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Part 15-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-qRv1wrtgsmM.mp4 113.43 MB
Part 15-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-i3RTW83wI1Q.mp4 107.2 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/07. Coding-zhQYREUI8Z0.mp4 105.02 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/08. Coding 2-qEteyPNRSwU.mp4 104.62 MB
Part 16-Module 01-Lesson 06_Datasets and Questions/01. Introduction-TdopVWltgqM.mp4 87.9 MB
Part 15-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-Zyq0FQ0XO3o.mp4 56.63 MB
Part 15-Module 01-Lesson 05_Interview Practice/04. Query a SQL database-UVSFLWdAKl4.mp4 51.16 MB
Part 15-Module 01-Lesson 03_Interview Fails/04. Interviewing Fails Lyla Fujiwara-CgK2HxdJzc8.mp4 49.74 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study-ahaxt6UKxQw.mp4 49.6 MB
Part 03-Module 04-Lesson 01_Investigate a Dataset/05. Investigate A Dataset Project Walkthrough Final-OtDZCYxbHB4.mp4 49.39 MB
Part 15-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-cXluuqCVg18.mp4 42.14 MB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/06. A Problem and How You Dealt With It-7IKqdW30GvQ.mp4 40.68 MB
Part 16-Module 01-Lesson 06_Datasets and Questions/03. Accuracy vs. Training Set Size-9w1Yi5nMNgw.mp4 34.84 MB
Part 07-Module 01-Lesson 01_What is EDA/09. Aude Explores Coordinated Migration-7ihp6ofAJG8.mp4 34.67 MB
Part 15-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-Uy89Ff49pRc.mp4 33.28 MB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.mp4 32.54 MB
Part 16-Module 01-Lesson 13_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.mp4 32.42 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.mp4 31.66 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.mp4 31.04 MB
Part 16-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn-COVRSk0GDEE.mp4 30.53 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/05. DAP Overview-qdV4sifMmWI.mp4 25.43 MB
Part 01-Module 01-Lesson 02_The Life of a Data Analyst/03. Industry Interview Sinthuja-R5XBQ7dSz7w.mp4 25.32 MB
Part 16-Module 01-Lesson 02_Naive Bayes/01. ML in The Google Self-Driving Car-lL16AQItG1g.mp4 25.09 MB
Part 12-Module 01-Lesson 01_GitHub Review/13. Interview with Art - Part 3-M6PKr3S1rPg.mp4 25.04 MB
Part 08-Module 03-Lesson 01_Assessing Data/15. Quality Programatic Assessment 1-l-FhDkQRclA.mp4 24.89 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/04. Recursion-_aI2Jch6Epk.mp4 24.68 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.mp4 23.75 MB
Part 16-Module 01-Lesson 09_Clustering/12. Sklearn-3zHUAXcoZ7c.mp4 23.31 MB
Part 04-Module 01-Lesson 16_Logistic Regression/29. Model Diagnostics In Python-1Z4eorbfOOc.mp4 22.79 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.mp4 22.1 MB
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.mp4 22.05 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.mp4 21.97 MB
Part 16-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.mp4 21.86 MB
Part 12-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.mp4 21.79 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.mp4 21.62 MB
Part 07-Module 01-Lesson 01_What is EDA/04. Why learn EDA-YM68DrqJw1I.mp4 20.99 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.mp4 20.96 MB
Part 16-Module 01-Lesson 13_PCA/28. PCA in sklearn-SBYdqlLgbGk.mp4 20.88 MB
Part 16-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.mp4 20.77 MB
Part 15-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.mp4 20.72 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.mp4 20.71 MB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.mp4 20.63 MB
Part 15-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.mp4 20.32 MB
Part 16-Module 01-Lesson 02_Naive Bayes/18. Gaussian NB Example-wpnDwiqTCJA.mp4 20.28 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.mp4 20.12 MB
Part 02-Module 02-Lesson 01_Python Project/08. Classroom DAND-Explore US Bikeshare Data Walkthrough-0yuglNRWyKs.mp4 20.12 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/04. David's Data Wrangling Example-TN-CWy3GK44.mp4 20.05 MB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson-nWFJ_eOU27I.mp4 19.94 MB
Part 18-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.mp4 19.91 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.mp4 19.91 MB
Part 16-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-GdsLRKjjKLw.mp4 19.32 MB
Part 16-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.mp4 19.3 MB
Part 16-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.mp4 19.11 MB
Part 08-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 Solution-CWJZoi_Es84.mp4 19.01 MB
Part 18-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.mp4 18.95 MB
Part 07-Module 02-Lesson 01_Explore and Summarize Data/06. Explore And Summarize Data Walkthrough Final-_OwKKL6SI38.mp4 18.9 MB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/05. Tableau Dashboards Stories with Trina-i9xslfFp80g.mp4 18.83 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/25. Smoothing Conditional Means-hxk2cgdChUw.mp4 18.8 MB
Part 18-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.mp4 18.44 MB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.mp4 18.44 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/05. How Does MLR Work-bvM6eUYyurA.mp4 18.43 MB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.mp4 18.41 MB
Part 15-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.mp4 18.38 MB
Part 07-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.mp4 18.32 MB
Part 01-Module 01-Lesson 02_The Life of a Data Analyst/04. Lada's Money Bag Meme - Data Analysis with R-Isa_FGQrvgs.mp4 18.32 MB
Part 18-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.mp4 18.28 MB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.mp4 18.22 MB
Part 16-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.mp4 18.11 MB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.mp4 18.01 MB
Part 16-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.mp4 17.6 MB
Part 16-Module 01-Lesson 13_PCA/29. When to Use PCA-hJZHcmJBk1o.mp4 17.53 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/17. Multicollinearity VIFs-wbtrXMusDe8.mp4 17.52 MB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.mp4 17.37 MB
Part 18-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.mp4 17.37 MB
Part 16-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data-TgkBAtaTqJk.mp4 17.36 MB
Part 16-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-4GBJk6R0pb4.mp4 17.31 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.mp4 17.27 MB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/11. Subquery Solution Video-Y6S3S0LsMrw.mp4 17.26 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.mp4 17.26 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.mp4 17.26 MB
Part 18-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.mp4 16.99 MB
Part 16-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.mp4 16.93 MB
Part 04-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.mp4 16.86 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.mp4 16.81 MB
Part 16-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.mp4 16.76 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.mp4 16.72 MB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.mp4 16.67 MB
Part 16-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn-aCdg-d_476Y.mp4 16.66 MB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.mp4 16.57 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/11. Efficiency of Merge Sort-HKiK5Y-YSkk.mp4 16.53 MB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. Creating Customer Segmentation Arvato Project-VCChvqoK6Go.mp4 16.45 MB
Part 01-Module 01-Lesson 02_The Life of a Data Analyst/01. Sparta Science-MkjoaUmdOXc.mp4 16.28 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.mp4 16.17 MB
Part 15-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.mp4 16.14 MB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.mp4 16.13 MB
Part 16-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.mp4 16.11 MB
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.mp4 15.95 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.mp4 15.95 MB
Part 08-Module 02-Lesson 01_Gathering Data/10. HTML Files in Python 1-0VZumC18UvQ.mp4 15.94 MB
Part 18-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.mp4 15.93 MB
Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.mp4 15.89 MB
Part 04-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.mp4 15.78 MB
Part 18-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.mp4 15.71 MB
Part 16-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.mp4 15.5 MB
Part 18-Module 01-Lesson 04_Functions/02. Defining Functions-IP_tJYhynbc.mp4 15.48 MB
Part 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.mp4 15.42 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.mp4 15.41 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.mp4 15.33 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.mp4 15.33 MB
Part 07-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.mp4 15.32 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.mp4 15.3 MB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.mp4 15.22 MB
Part 16-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.mp4 15.2 MB
Part 08-Module 04-Lesson 01_Cleaning Data/17. Flashforward-rfMu3f9O9hQ.mp4 15.17 MB
Part 18-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.mp4 15.06 MB
Part 15-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.mp4 15 MB
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.mp4 14.97 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/07. Finding the First Link-_bPdJBJtNqo.mp4 14.94 MB
Part 16-Module 01-Lesson 10_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.mp4 14.9 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.mp4 14.72 MB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/01. Introduction-ICKBWIkfeJ8.mp4 14.59 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/10. Merge Sort-K916wfSzKxE.mp4 14.59 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.mp4 14.57 MB
Part 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.mp4 14.57 MB
Part 07-Module 01-Lesson 01_What is EDA/02. Data is Ubiquitous-YbVuN2KOlt4.mp4 14.57 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.mp4 14.51 MB
Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.mp4 14.42 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.mp4 14.42 MB
Part 15-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.mp4 14.4 MB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.mp4 14.38 MB
Part 15-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.mp4 14.28 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.mp4 14.19 MB
Part 15-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.mp4 14.02 MB
Part 16-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.mp4 13.94 MB
Part 08-Module 03-Lesson 01_Assessing Data/09. Quality Visual Assessment 1 -XfKc5PtJ7cc.mp4 13.89 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Beautiful Soup Demonstration-dk7ESZXLnk4.mp4 13.87 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.mp4 13.78 MB
Part 01-Module 01-Lesson 02_The Life of a Data Analyst/02. Interview with a Data Scientist-kNnFA5hxI2Q.mp4 13.77 MB
Part 14-Module 01-Lesson 01_Conduct a Job Search/03. Target Your Application to An Employer-X9JBzbrkcvs.mp4 13.74 MB
Part 08-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.mp4 13.64 MB
Part 08-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.mp4 13.64 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.mp4 13.4 MB
Part 16-Module 01-Lesson 07_Regressions/27. Problem with Minimizing Absolute Errors-U46D7oEijlI.mp4 13.39 MB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.mp4 13.38 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.mp4 13.37 MB
Part 16-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.mp4 13.36 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.mp4 13.33 MB
Part 16-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.mp4 13.29 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.mp4 13.27 MB
Part 16-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.mp4 13.26 MB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4 13.24 MB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4 13.24 MB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4 13.24 MB
Part 18-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.mp4 13.22 MB
Part 12-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.mp4 13.17 MB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/05. Ud1110 IntroPy L212 Put A Python In Your Computer-P-Lr3WED7pg.mp4 13.11 MB
Part 08-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 1-nDWAZOU3W3U.mp4 12.99 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.mp4 12.95 MB
Part 16-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.mp4 12.86 MB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.mp4 12.85 MB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.mp4 12.85 MB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.mp4 12.85 MB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.mp4 12.85 MB
Part 18-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.mp4 12.78 MB
Part 16-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.mp4 12.68 MB
Part 16-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.mp4 12.67 MB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.mp4 12.64 MB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.mp4 12.64 MB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.mp4 12.64 MB
Part 16-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.mp4 12.62 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.mp4 12.55 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.mp4 12.54 MB
Part 04-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.mp4 12.52 MB
Part 16-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.mp4 12.5 MB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.mp4 12.48 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/01. Welcome!-KJT4Z0xpHns.mp4 12.36 MB
Part 11-Module 01-Lesson 03_Review a Repo's History/01. A Repository's History - Intro-UBmg3syQS0E.mp4 12.31 MB
Part 15-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.mp4 12.24 MB
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.mp4 12.19 MB
Part 16-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.mp4 12.19 MB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.mp4 12.18 MB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.mp4 12.18 MB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.mp4 12.18 MB
Part 16-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.mp4 12.12 MB
Part 14-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.mp4 12.08 MB
Part 16-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.mp4 12.06 MB
Part 16-Module 01-Lesson 07_Regressions/31. R Squared in SKlearn-Dxf1I4IE6co.mp4 12.04 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.mp4 12 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/02. Efficiency of Binary Search-7WbRB7dSyvc.mp4 11.97 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/24. What If Our Sample Is Large-WoTCeSTL1eM.mp4 11.95 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.mp4 11.94 MB
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.mp4 11.87 MB
Part 15-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.mp4 11.85 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Using Python to get HTML-1Y_CZyKNWe4.mp4 11.82 MB
Part 16-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.mp4 11.81 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.mp4 11.79 MB
Part 16-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.mp4 11.76 MB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.mp4 11.71 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-MV_e0z9kFjM.mp4 11.63 MB
Part 07-Module 01-Lesson 01_What is EDA/05. Aude's Interest in Data-DDNSMG_RltY.mp4 11.61 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.mp4 11.56 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/01. Ud1110 IntroPy L5 01 A Wikipedia Crawl-osrplIl1m-k.mp4 11.56 MB
Part 04-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.mp4 11.54 MB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.mp4 11.53 MB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.mp4 11.53 MB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.mp4 11.53 MB
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.mp4 11.53 MB
Part 16-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.mp4 11.52 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/08. Types Of Errors - Part II-mbdSQ5CjdFs.mp4 11.48 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.mp4 11.47 MB
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.mp4 11.42 MB
Part 08-Module 02-Lesson 01_Gathering Data/10. HTML Files In Python 2-3caDGTxcoCw.mp4 11.41 MB
Part 08-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1-5UYGvKDsd-M.mp4 11.41 MB
Part 18-Module 01-Lesson 05_Scripting/20. Importing Files-qjeSn6zZbR0.mp4 11.41 MB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.mp4 11.32 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.mp4 11.32 MB
Part 04-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.mp4 11.26 MB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.mp4 11.26 MB
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.mp4 11.22 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.mp4 11.18 MB
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.mp4 11.08 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.mp4 11.07 MB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.mp4 11.04 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.mp4 10.99 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.mp4 10.98 MB
Part 04-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.mp4 10.96 MB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.mp4 10.92 MB
Part 18-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.mp4 10.89 MB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.mp4 10.82 MB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.mp4 10.81 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/12. Common Types of Hypothesis Tests-8hv8KnvQ6JY.mp4 10.8 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Exploring HTML with Developer Tools-YWbCvLCBQrg.mp4 10.8 MB
Part 04-Module 01-Lesson 16_Logistic Regression/01. Introduction to Logistic Regression-P_f2RjjnPEg.mp4 10.77 MB
Part 07-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-v4UGBUB6jO4.mp4 10.76 MB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/09. SQL Subquery Video-10pmKmTI_CA.mp4 10.75 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.mp4 10.75 MB
Part 15-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.mp4 10.71 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/31. L2 02 Dictionaries And Identiy Operators V3-QR8HTxCTWi0.mp4 10.7 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.mp4 10.68 MB
Part 16-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.mp4 10.67 MB
Part 07-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.mp4 10.64 MB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.mp4 10.61 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/17. Cleaning Example-7bnSPYtPDzQ.mp4 10.56 MB
Part 18-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.mp4 10.55 MB
Part 16-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.mp4 10.53 MB
Part 14-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.mp4 10.45 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.mp4 10.43 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.mp4 10.37 MB
Part 08-Module 02-Lesson 01_Gathering Data/06. Flat File Structure-bLKVRIhrZUY.mp4 10.34 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.mp4 10.33 MB
Part 11-Module 01-Lesson 01_What is Version Control/03. Gitfinal L1 13 Git'S Terminology-bf26adzeqMM.mp4 10.33 MB
Part 16-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.mp4 10.32 MB
Part 03-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.mp4 10.29 MB
Part 07-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.mp4 10.25 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.mp4 10.23 MB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/05. A Faster Algorithm-J7S3CHFBZJA.mp4 10.22 MB
Part 16-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.mp4 10.16 MB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. Kaggle Project Final For Classroom-Ssttix340C8.mp4 10.15 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.mp4 10.15 MB
Part 16-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.mp4 10.15 MB
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.mp4 10.14 MB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/12. Meet the Careers Team-cuKecPpZ7PM.mp4 10.12 MB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/13. Meet the Careers Team-cuKecPpZ7PM.mp4 10.12 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.mp4 10.07 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.mp4 10.07 MB
Part 16-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.mp4 10.05 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.mp4 9.99 MB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.mp4 9.98 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.mp4 9.92 MB
Part 16-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.mp4 9.9 MB
Part 08-Module 02-Lesson 01_Gathering Data/03. Finding the Best Movies-aq3qM2EkwrI.mp4 9.89 MB
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.mp4 9.87 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.mp4 9.82 MB
Part 07-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.mp4 9.82 MB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.mp4 9.81 MB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.mp4 9.8 MB
Part 07-Module 01-Lesson 01_What is EDA/06. Goals of EDA-NEvuulahg2g.mp4 9.78 MB
Part 09-Module 01-Lesson 02_Design/08. Data Ink Ratio-gW2FapuYV4A.mp4 9.78 MB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/02. DSND Trailer Final-X2xQnb-bR8A.mp4 9.77 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.mp4 9.77 MB
Part 16-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.mp4 9.76 MB
Part 04-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.mp4 9.74 MB
Part 04-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.mp4 9.7 MB
Part 16-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.mp4 9.67 MB
Part 07-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.mp4 9.67 MB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.mp4 9.59 MB
Part 12-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.mp4 9.59 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.mp4 9.55 MB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.mp4 9.49 MB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.mp4 9.49 MB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.mp4 9.49 MB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.mp4 9.47 MB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.mp4 9.46 MB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.mp4 9.46 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.mp4 9.43 MB
Part 15-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-wkWDrSBBtz0.mp4 9.43 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.mp4 9.4 MB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/11. Time Commitment-d-VfUw7wNEQ.mp4 9.38 MB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/10. Time Commitment-d-VfUw7wNEQ.mp4 9.38 MB
Part 16-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.mp4 9.32 MB
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.mp4 9.32 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-FC_GNjqj5zI.mp4 9.3 MB
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.mp4 9.25 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.mp4 9.25 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.mp4 9.24 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.mp4 9.24 MB
Part 02-Module 01-Lesson 03_Data Structures and Loops/18. Problem Solving Skills-el9knzvU4TM.mp4 9.19 MB
Part 09-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.mp4 9.12 MB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/09. Matrix Transposes-NVK5xCY3CZE.mp4 9.09 MB
Part 07-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.mp4 9.03 MB
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.mp4 9.02 MB
Part 18-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.mp4 9.01 MB
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.mp4 8.96 MB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.mp4 8.93 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.mp4 8.92 MB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.mp4 8.92 MB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro-xHwIU4j3gBc.mp4 8.9 MB
Part 11-Module 01-Lesson 01_What is Version Control/01. Gitfinal L1 01 Welcome-lbR82UD5F0c.mp4 8.89 MB
Part 15-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.mp4 8.87 MB
Part 18-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.mp4 8.85 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 43 Case Study Review-jiZwuN6zTFs.mp4 8.81 MB
Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.mp4 8.77 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (After Cleaning)-OF2486euiRE.mp4 8.7 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.mp4 8.7 MB
Part 08-Module 03-Lesson 01_Assessing Data/07. Visual Assessment -GVVibuIg3Ro.mp4 8.68 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.mp4 8.66 MB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.mp4 8.63 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/20. Connecting Errors and P-Values-hFNjd5l9CLs.mp4 8.58 MB
Part 08-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.mp4 8.56 MB
Part 16-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.mp4 8.56 MB
Part 09-Module 01-Lesson 02_Design/13. Using Color-6bAedqD3ilw.mp4 8.47 MB
Part 18-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.mp4 8.37 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.mp4 8.37 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.mp4 8.33 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.mp4 8.32 MB
Part 08-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment -BNRJdhA8_s8.mp4 8.27 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.mp4 8.26 MB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.mp4 8.24 MB
Part 07-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.mp4 8.23 MB
Part 09-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.mp4 8.22 MB
Part 15-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.mp4 8.22 MB
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.mp4 8.2 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.mp4 8.19 MB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.mp4 8.19 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.mp4 8.17 MB
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.mp4 8.13 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.mp4 8.12 MB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet -K-Owid_mf8o.mp4 8.07 MB
Part 08-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 Solution-E5tAoCK6GcQ.mp4 8.03 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question-xQJyObqxg3E.mp4 8.03 MB
Part 16-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.mp4 8.01 MB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.mp4 7.99 MB
Part 18-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.mp4 7.99 MB
Part 16-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.mp4 7.95 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.mp4 7.94 MB
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.mp4 7.92 MB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.mp4 7.91 MB
Part 05-Module 01-Lesson 01_Congratulations & Next Steps/img/party-v1-1.gif 7.88 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/07. Bubble Sort-h_osLG3GmjE.mp4 7.88 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/10. Traditional Confidence Interval Methods-DmZwYHuz2eM.mp4 7.87 MB
Part 16-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.mp4 7.86 MB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.mp4 7.84 MB
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.mp4 7.83 MB
Part 15-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.mp4 7.77 MB
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.mp4 7.76 MB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.mp4 7.74 MB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-resolve-merge-conflict.gif 7.73 MB
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.mp4 7.71 MB
Part 16-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.mp4 7.7 MB
Part 16-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK-gWbkW_cyNs8.mp4 7.69 MB
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.mp4 7.69 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/04. Setting Up Hypotheses - Part II-nByvHz77GiA.mp4 7.67 MB
Part 18-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.mp4 7.65 MB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.mp4 7.64 MB
Part 15-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.mp4 7.62 MB
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.mp4 7.62 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.mp4 7.61 MB
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.mp4 7.61 MB
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.mp4 7.61 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.mp4 7.59 MB
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.mp4 7.59 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.mp4 7.55 MB
Part 04-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.mp4 7.54 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.mp4 7.52 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/29. 11 CASE V2-BInXuTY_FzE.mp4 7.52 MB
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.mp4 7.52 MB
Part 03-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.mp4 7.51 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.mp4 7.5 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.mp4 7.49 MB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/01. Adding Commits To A Repo - Intro-sLcOFQ4mGvo.mp4 7.48 MB
Part 04-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.mp4 7.48 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/21. Conclusions In Hypothesis Testing-I0Mo7hcxahY.mp4 7.48 MB
Part 07-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.mp4 7.43 MB
Part 18-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.mp4 7.42 MB
Part 16-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.mp4 7.41 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.mp4 7.41 MB
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.mp4 7.38 MB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/06. Dynamic Programming-VQeFcG9pjJU.mp4 7.37 MB
Part 18-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.mp4 7.36 MB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Welcome to Introduction to Python Programming-IILB-5hIeZM.mp4 7.34 MB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2-8jtk8BzBdj8.mp4 7.34 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/25. Multiple Testing Corrections-DuMgeHrkIF0.mp4 7.33 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.mp4 7.32 MB
Part 16-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.mp4 7.31 MB
Part 16-Module 01-Lesson 07_Regressions/37. Regression Mini-Project Video-CrD9jN3rBM8.mp4 7.3 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.mp4 7.29 MB
Part 15-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.mp4 7.29 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/16. What Is A P-value Anyway-eU6pUZjqviA.mp4 7.27 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.mp4 7.25 MB
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.mp4 7.25 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.mp4 7.25 MB
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.mp4 7.22 MB
Part 08-Module 02-Lesson 01_Gathering Data/20. Flashforward 2-Sbyn8aT-8G8.mp4 7.22 MB
Part 07-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.mp4 7.22 MB
Part 08-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.mp4 7.22 MB
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.mp4 7.2 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.mp4 7.14 MB
Part 08-Module 02-Lesson 01_Gathering Data/16. JSON File Structure-hO2CayzZBoA.mp4 7.14 MB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/01. Jupyter-qiYDWFLyXvg.mp4 7.12 MB
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.mp4 7.1 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.mp4 7.09 MB
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.mp4 7.08 MB
Part 08-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces) 2-tobH58uO24U.mp4 7.06 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.mp4 7.04 MB
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.mp4 7.02 MB
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-GuBics_6HOk.mp4 7 MB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.mp4 6.99 MB
Part 16-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.mp4 6.98 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/26. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.mp4 6.98 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.mp4 6.98 MB
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.mp4 6.96 MB
Part 16-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.mp4 6.95 MB
Part 12-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.mp4 6.92 MB
Part 16-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.mp4 6.92 MB
Part 07-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.mp4 6.91 MB
Part 15-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.mp4 6.85 MB
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.mp4 6.82 MB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.mp4 6.81 MB
Part 11-Module 01-Lesson 02_Create A Git Repo/01. Creating New Repositories - Intro-KT163BkqIeg.mp4 6.8 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.mp4 6.8 MB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.mp4 6.79 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Standard Deviation Calculation-H5zA1A-XPoY.mp4 6.78 MB
Part 09-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.mp4 6.78 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.mp4 6.74 MB
Part 16-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.mp4 6.73 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.mp4 6.73 MB
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.mp4 6.72 MB
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.mp4 6.72 MB
Part 18-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.mp4 6.71 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.mp4 6.71 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import-tU1N-8aNB_M.mp4 6.69 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.mp4 6.69 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function-iJEBxsKDDoE.mp4 6.68 MB
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.mp4 6.68 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/22. Looking at Samples of Households-kQePh6UTB90.mp4 6.65 MB
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.mp4 6.64 MB
Part 15-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.mp4 6.63 MB
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.mp4 6.61 MB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/01. Tagging, Branching, And Merging - Intro-sMf_r4_z-Ls.mp4 6.59 MB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/02. What's Ahead-ggbCydfI1JM.mp4 6.59 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.mp4 6.58 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.mp4 6.58 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.mp4 6.57 MB
Part 07-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.mp4 6.57 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2-ZXy8jgywY5g.mp4 6.56 MB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.mp4 6.54 MB
Part 04-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.mp4 6.54 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.mp4 6.54 MB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.mp4 6.52 MB
Part 16-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.mp4 6.51 MB
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.mp4 6.5 MB
Part 09-Module 01-Lesson 02_Design/09. Design Integrity-y72_fVFtqlY.mp4 6.48 MB
Part 15-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.mp4 6.48 MB
Part 15-Module 02-Lesson 02_List-Based Collections/03. Arrays-OnPP5xDmFv0.mp4 6.45 MB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.mp4 6.42 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-3kH4ei9l4h8.mp4 6.4 MB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.mp4 6.34 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.mp4 6.33 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.mp4 6.32 MB
Part 16-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.mp4 6.31 MB
Part 07-Module 01-Lesson 02_R Basics/10. Read and Subset Data-UdniaeLsViQ.mp4 6.31 MB
Part 11-Module 01-Lesson 06_Undoing Changes/01. Undoing Changes - Intro-Kfi7l41wUVc.mp4 6.31 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.mp4 6.3 MB
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.mp4 6.3 MB
Part 15-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.mp4 6.27 MB
Part 04-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.mp4 6.27 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.mp4 6.26 MB
Part 15-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.mp4 6.26 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.mp4 6.24 MB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.mp4 6.22 MB
Part 16-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.mp4 6.22 MB
Part 07-Module 01-Lesson 01_What is EDA/10. Course Overview-W8N0aSMPff8.mp4 6.2 MB
Part 11-Module 01-Lesson 03_Review a Repo's History/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 42 Git Log -P Output Walkthru-A8Kwocr-K8c.mp4 6.19 MB
Part 16-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.mp4 6.18 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.mp4 6.17 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.mp4 6.17 MB
Part 09-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.mp4 6.14 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort-kUon6854joI.mp4 6.1 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.mp4 6.09 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.mp4 6.08 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 34 Finding The First Link 2-bsMtF-705EU.mp4 6.07 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/22. L2 08 Lists And Membership Operators V2-JAbZdZg5_x8.mp4 6.06 MB
Part 09-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.mp4 6.05 MB
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.mp4 6.05 MB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.mp4 6.04 MB
Part 07-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.mp4 6.03 MB
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.mp4 6.02 MB
Part 16-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.mp4 6.01 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.mp4 6.01 MB
Part 16-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.mp4 6.01 MB
Part 15-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.mp4 6 MB
Part 15-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.mp4 5.99 MB
Part 15-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.mp4 5.99 MB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.mp4 5.98 MB
Part 07-Module 01-Lesson 01_What is EDA/03. Go Exploring-dias-YUpewk.mp4 5.97 MB
Part 09-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.mp4 5.97 MB
Part 16-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.mp4 5.95 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.mp4 5.92 MB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.mp4 5.92 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.mp4 5.92 MB
Part 09-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.mp4 5.91 MB
Part 18-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.mp4 5.9 MB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.mp4 5.89 MB
Part 03-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.mp4 5.89 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/02. Introduction-Z8WNfx9Oq9s.mp4 5.88 MB
Part 03-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.mp4 5.88 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/07. Ud1110 IntroPy L5 30 Finding The First Link-Z-uuXDrMzqM.mp4 5.87 MB
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.mp4 5.84 MB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. What are we going to do-rK6YlbBiKQM.mp4 5.84 MB
Part 07-Module 01-Lesson 01_What is EDA/08. Our Approach for This Course-dBsf-szQ00s.mp4 5.83 MB
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.mp4 5.83 MB
Part 16-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.mp4 5.83 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/party.gif 5.82 MB
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.mp4 5.79 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.mp4 5.79 MB
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.mp4 5.77 MB
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.mp4 5.75 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-Och80L_uNjU.mp4 5.75 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.mp4 5.74 MB
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.mp4 5.72 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.mp4 5.72 MB
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.mp4 5.7 MB
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.mp4 5.69 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/22. L2 09 Lists And Membership Operators V2-rNV_E50wcWM.mp4 5.67 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.mp4 5.66 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/20. Notation for Random Variables-8NxTW1u4s-Y.mp4 5.66 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.mp4 5.66 MB
Part 18-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.mp4 5.64 MB
Part 16-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.mp4 5.63 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.mp4 5.63 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/13. LIMIT Statement-cCPHNNhBgpQ.mp4 5.62 MB
Part 03-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.mp4 5.62 MB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.mp4 5.61 MB
Part 15-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.mp4 5.61 MB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.mp4 5.6 MB
Part 18-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.mp4 5.58 MB
Part 08-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.mp4 5.58 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.mp4 5.56 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-a2GCyz_N0oY.mp4 5.56 MB
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.mp4 5.55 MB
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.mp4 5.52 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/24. Final Thoughts-CNGDocH1k3k.mp4 5.5 MB
Part 16-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.mp4 5.49 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.mp4 5.49 MB
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.mp4 5.49 MB
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.mp4 5.47 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.mp4 5.46 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.mp4 5.46 MB
Part 15-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.mp4 5.43 MB
Part 16-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.mp4 5.42 MB
Part 08-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.mp4 5.42 MB
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.mp4 5.41 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.mp4 5.39 MB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.mp4 5.38 MB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.mp4 5.37 MB
Part 04-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.mp4 5.37 MB
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.mp4 5.37 MB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.mp4 5.36 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.mp4 5.35 MB
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.mp4 5.35 MB
Part 09-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.mp4 5.35 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.mp4 5.34 MB
Part 18-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.mp4 5.33 MB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/08. Integrity and Mindset-zCOr3O50gQM.mp4 5.32 MB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/07. Integrity and Mindset-zCOr3O50gQM.mp4 5.32 MB
Part 03-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.mp4 5.32 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.mp4 5.31 MB
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.mp4 5.31 MB
Part 08-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.mp4 5.3 MB
Part 16-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.mp4 5.29 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.mp4 5.28 MB
Part 16-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.mp4 5.27 MB
Part 03-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.mp4 5.26 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/03. Parch Posey Database-JOMI560DgXg.mp4 5.26 MB
Part 04-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.mp4 5.26 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.mp4 5.25 MB
Part 16-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.mp4 5.25 MB
Part 18-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.mp4 5.25 MB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.mp4 5.23 MB
Part 08-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.mp4 5.23 MB
Part 08-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.mp4 5.22 MB
Part 04-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.mp4 5.21 MB
Part 18-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.mp4 5.21 MB
Part 16-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.mp4 5.21 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.mp4 5.2 MB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/02. Projects Term 2-jSRJblo-Ptw.mp4 5.2 MB
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.mp4 5.19 MB
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.mp4 5.18 MB
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.mp4 5.17 MB
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.mp4 5.14 MB
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.mp4 5.13 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.mp4 5.11 MB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.mp4 5.1 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.mp4 5.08 MB
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.mp4 5.08 MB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.mp4 5.07 MB
Part 08-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.mp4 5.07 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/09. SELECT FROM Statements-urOYuuav4BY.mp4 5.07 MB
Part 03-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.mp4 5.07 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/10. The Completed Program-yGDHoIOfwt8.mp4 5.06 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.mp4 5.06 MB
Part 16-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.mp4 5.05 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.mp4 5.05 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.mp4 5.03 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.mp4 5.03 MB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 18 Recap-xqD9ImXXXHk.mp4 5.03 MB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.mp4 5.02 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.mp4 5.02 MB
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.mp4 5.02 MB
Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.mp4 5.01 MB
Part 18-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.mp4 5 MB
Part 16-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.mp4 4.97 MB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/07. Outro-5eyvsMvAPYs.mp4 4.96 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.mp4 4.92 MB
Part 08-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.mp4 4.92 MB
Part 16-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.mp4 4.9 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.mp4 4.9 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.mp4 4.89 MB
Part 08-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.mp4 4.89 MB
Part 09-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.mp4 4.89 MB
Part 16-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.mp4 4.89 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.mp4 4.88 MB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.mp4 4.87 MB
Part 12-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.mp4 4.86 MB
Part 07-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.mp4 4.84 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/22. L2 07 Lists And Membership Operators II V3-3Nj-b-ZzqH8.mp4 4.83 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.mp4 4.83 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.mp4 4.82 MB
Part 16-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.mp4 4.82 MB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.mp4 4.81 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.mp4 4.8 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.mp4 4.8 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.mp4 4.8 MB
Part 08-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.mp4 4.8 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.mp4 4.78 MB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.mp4 4.77 MB
Part 16-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video-68EGMItJiNM.mp4 4.74 MB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.mp4 4.74 MB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.mp4 4.73 MB
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.mp4 4.71 MB
Part 08-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.mp4 4.71 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/04. Ud1110 IntroPy L5 22 Continue Crawl Solution-tLhTfSZ6LRA.mp4 4.7 MB
Part 09-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.mp4 4.68 MB
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.mp4 4.68 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.mp4 4.67 MB
Part 16-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.mp4 4.67 MB
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.mp4 4.67 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.mp4 4.66 MB
Part 04-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.mp4 4.66 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.mp4 4.66 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.mp4 4.66 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.mp4 4.66 MB
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.mp4 4.64 MB
Part 16-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.mp4 4.63 MB
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.mp4 4.63 MB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.mp4 4.62 MB
Part 08-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.mp4 4.62 MB
Part 15-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.mp4 4.61 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.mp4 4.61 MB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.mp4 4.61 MB
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.mp4 4.61 MB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/07. Projects and Progress-Z9ZLMQWsbsk.mp4 4.6 MB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/06. Projects and Progress-Z9ZLMQWsbsk.mp4 4.6 MB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.mp4 4.59 MB
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.mp4 4.59 MB
Part 16-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.mp4 4.59 MB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.mp4 4.59 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.mp4 4.58 MB
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.mp4 4.57 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.mp4 4.56 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.mp4 4.56 MB
Part 08-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.mp4 4.56 MB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.mp4 4.55 MB
Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.mp4 4.54 MB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.mp4 4.52 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.mp4 4.51 MB
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.mp4 4.51 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.mp4 4.51 MB
Part 03-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.mp4 4.5 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/22. WHERE Statements -mN0uTnlXaxg.mp4 4.5 MB
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.mp4 4.5 MB
Part 07-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.mp4 4.5 MB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/06. Ud1110 IntroPy L218 My Python Programming Setup-wrnov8J5zto.mp4 4.48 MB
Part 15-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.mp4 4.48 MB
Part 18-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.mp4 4.48 MB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.mp4 4.48 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.mp4 4.47 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-28iU6GrDVfU.mp4 4.47 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.mp4 4.46 MB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.mp4 4.46 MB
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.mp4 4.45 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.mp4 4.45 MB
Part 16-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.mp4 4.44 MB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.mp4 4.42 MB
Part 04-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.mp4 4.4 MB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/09. How Does Project Submission Work-jCJa_VP6qgg.mp4 4.4 MB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/08. How Does Project Submission Work-jCJa_VP6qgg.mp4 4.4 MB
Part 11-Module 01-Lesson 01_What is Version Control/01. Gitfinal L1 03 Version Control Systems-b7TjsVoTo3Q.mp4 4.39 MB
Part 11-Module 01-Lesson 03_Review a Repo's History/07. A Repository's History - Outro-9rUf2HbdAd8.mp4 4.39 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/29. Hypothesis Testing Conclusion-nQFchD4XPPs.mp4 4.36 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/04. 29 Number Summary-gzUN5zKLHjQ.mp4 4.36 MB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.mp4 4.36 MB
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.mp4 4.36 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.mp4 4.36 MB
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.mp4 4.36 MB
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.mp4 4.35 MB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.mp4 4.34 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.mp4 4.34 MB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.mp4 4.33 MB
Part 07-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.mp4 4.33 MB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.mp4 4.29 MB
Part 08-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.mp4 4.27 MB
Part 16-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.mp4 4.27 MB
Part 04-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.mp4 4.26 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/16. Precision and Recall-3vT0kSBCLdU.mp4 4.26 MB
Part 15-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.mp4 4.26 MB
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.mp4 4.26 MB
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.mp4 4.25 MB
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.mp4 4.25 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.mp4 4.25 MB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.mp4 4.24 MB
Part 18-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.mp4 4.24 MB
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.mp4 4.24 MB
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.mp4 4.23 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.mp4 4.23 MB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 27 Confession Corner-xtsugblSwrU.mp4 4.23 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.mp4 4.23 MB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.mp4 4.22 MB
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.mp4 4.22 MB
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.mp4 4.22 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.mp4 4.22 MB
Part 04-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.mp4 4.21 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.mp4 4.21 MB
Part 04-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.mp4 4.21 MB
Part 15-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.mp4 4.2 MB
Part 15-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.mp4 4.19 MB
Part 07-Module 01-Lesson 01_What is EDA/02. Data is Ubiquitous-ieiQqLicBjg.mp4 4.19 MB
Part 03-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.mp4 4.19 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.mp4 4.19 MB
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.mp4 4.19 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.mp4 4.18 MB
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.mp4 4.18 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.mp4 4.18 MB
Part 16-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.mp4 4.16 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.mp4 4.16 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.mp4 4.15 MB
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.mp4 4.15 MB
Part 15-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.mp4 4.13 MB
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.mp4 4.11 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.mp4 4.11 MB
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.mp4 4.1 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.mp4 4.09 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-hW_1ASU-j8A.mp4 4.09 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.mp4 4.09 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.mp4 4.09 MB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.mp4 4.08 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.mp4 4.06 MB
Part 16-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.mp4 4.06 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.mp4 4.05 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.mp4 4.05 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.mp4 4.04 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.mp4 4.03 MB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.mp4 4.03 MB
Part 18-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.mp4 4.03 MB
Part 08-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.mp4 4.03 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.mp4 4.02 MB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.mp4 4.02 MB
Part 16-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.mp4 4.02 MB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.mp4 4.01 MB
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.mp4 4.01 MB
Part 16-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.mp4 4 MB
Part 12-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.mp4 3.99 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.mp4 3.98 MB
Part 16-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.mp4 3.98 MB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.mp4 3.96 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.mp4 3.96 MB
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.mp4 3.95 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.mp4 3.95 MB
Part 07-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.mp4 3.95 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.mp4 3.95 MB
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.mp4 3.95 MB
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.mp4 3.95 MB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.mp4 3.94 MB
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.mp4 3.94 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Do Analysts Like SQL-uCNOtUht2Xc.mp4 3.94 MB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.mp4 3.94 MB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.mp4 3.94 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/10. Types Of Errors - Part III-Z-srkCPsdaM.mp4 3.94 MB
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.mp4 3.93 MB
Part 15-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.mp4 3.93 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/13. How Do We Choose Between Hypotheses-JkXTwS-5Daw.mp4 3.92 MB
Part 15-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.mp4 3.91 MB
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.mp4 3.91 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate-EpfoKAwV_Eg.mp4 3.9 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.mp4 3.89 MB
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.mp4 3.89 MB
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.mp4 3.87 MB
Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.mp4 3.87 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.mp4 3.87 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.mp4 3.86 MB
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.mp4 3.85 MB
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.mp4 3.85 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.mp4 3.85 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.mp4 3.85 MB
Part 04-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.mp4 3.84 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.mp4 3.84 MB
Part 08-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.mp4 3.83 MB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.mp4 3.83 MB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.mp4 3.82 MB
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.mp4 3.82 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.mp4 3.81 MB
Part 15-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.mp4 3.81 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.mp4 3.81 MB
Part 02-Module 01-Lesson 03_Data Structures and Loops/08. Ud1110 IntroPy L3 37 Reading Existing Code-0Pg3HryU9Z4.mp4 3.81 MB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.mp4 3.8 MB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/07. Outro-ot4fPX1jzOI.mp4 3.8 MB
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.mp4 3.8 MB
Part 16-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.mp4 3.79 MB
Part 08-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.mp4 3.79 MB
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.mp4 3.79 MB
Part 16-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.mp4 3.78 MB
Part 02-Module 01-Lesson 04_Files and Modules/10. Ud1110 IntroPy L4 99 Lesson Outro-8AOietAcOLk.mp4 3.78 MB
Part 08-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.mp4 3.78 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.mp4 3.77 MB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.mp4 3.77 MB
Part 11-Module 01-Lesson 01_What is Version Control/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 30 Configure Terminal-CCYjHfBk9hw.mp4 3.77 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/14. Simulating From the Null-sL2yJtHZd8Y.mp4 3.75 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.mp4 3.75 MB
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.mp4 3.75 MB
Part 16-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.mp4 3.75 MB
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.mp4 3.74 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.mp4 3.74 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/20. Hierarchies-wl_AM-spH68.mp4 3.74 MB
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.mp4 3.74 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.mp4 3.74 MB
Part 15-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.mp4 3.72 MB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.mp4 3.72 MB
Part 12-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.mp4 3.72 MB
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.mp4 3.72 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.mp4 3.71 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.mp4 3.7 MB
Part 07-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.mp4 3.69 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.mp4 3.69 MB
Part 15-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.mp4 3.68 MB
Part 15-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.mp4 3.68 MB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.mp4 3.68 MB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/01. Welcome To DAND Term 1-Q1GEXzXXLN0.mp4 3.68 MB
Part 04-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.mp4 3.67 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.mp4 3.67 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.mp4 3.67 MB
Part 08-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.mp4 3.66 MB
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.mp4 3.66 MB
Part 07-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.mp4 3.66 MB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.mp4 3.65 MB
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.mp4 3.65 MB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.mp4 3.65 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/17. Calculating the p-value-_W3Jg7jQ8jI.mp4 3.64 MB
Part 03-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.mp4 3.64 MB
Part 08-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.mp4 3.64 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/07. Types Of Statements-vLvJbIz94C4.mp4 3.64 MB
Part 11-Module 01-Lesson 01_What is Version Control/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 23 Configure Terminal-h00n9QLfbqU.mp4 3.63 MB
Part 15-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.mp4 3.63 MB
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.mp4 3.62 MB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.mp4 3.61 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.mp4 3.6 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.mp4 3.6 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.mp4 3.6 MB
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.mp4 3.59 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 37 Squashing Bugs-X-GqfxYpaw0.mp4 3.58 MB
Part 16-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.mp4 3.58 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.mp4 3.57 MB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 26 Branching Overview-ywcOC6CLG4s.mp4 3.55 MB
Part 08-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.mp4 3.55 MB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.mp4 3.55 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.mp4 3.54 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.mp4 3.54 MB
Part 08-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.mp4 3.53 MB
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Ud1110 IntroPy L1 53 Lesson 1 Done!-y3dstGZWPgc.mp4 3.52 MB
Part 11-Module 01-Lesson 01_What is Version Control/06. Onward-iXbMaTwfIJI.mp4 3.51 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.mp4 3.51 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.mp4 3.51 MB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.mp4 3.5 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.mp4 3.5 MB
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.mp4 3.5 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.mp4 3.49 MB
Part 15-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.mp4 3.49 MB
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Python Documentation-lBtG0DO_KqM.mp4 3.48 MB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/01. DAND 01 Congrats V1-QS1jKmZWdTk.mp4 3.48 MB
Part 08-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.mp4 3.48 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.mp4 3.48 MB
Part 15-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.mp4 3.48 MB
Part 04-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.mp4 3.48 MB
Part 08-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.mp4 3.47 MB
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.mp4 3.46 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.mp4 3.45 MB
Part 04-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.mp4 3.45 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.mp4 3.45 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.mp4 3.44 MB
Part 08-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.mp4 3.44 MB
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.mp4 3.42 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/13. Worksheets-2xRKvQTRtlk.mp4 3.41 MB
Part 04-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.mp4 3.41 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.mp4 3.41 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 44 Bye Bye!-lRYvuMf33eY.mp4 3.39 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/01. Intro Project Explore Weather Trends-xneztkf0TsY.mp4 3.39 MB
Part 16-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.mp4 3.39 MB
Part 18-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.mp4 3.39 MB
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.mp4 3.38 MB
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.mp4 3.37 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.mp4 3.37 MB
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.mp4 3.37 MB
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.mp4 3.37 MB
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.mp4 3.36 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.mp4 3.36 MB
Part 12-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.mp4 3.36 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.mp4 3.35 MB
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.mp4 3.35 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.mp4 3.35 MB
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.mp4 3.35 MB
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.mp4 3.34 MB
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.mp4 3.32 MB
Part 04-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.mp4 3.32 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.mp4 3.32 MB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/18. Ud1110 IntroPy L250 End Of Lesson 2-UhvyD_60esQ.mp4 3.31 MB
Part 12-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.mp4 3.3 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.mp4 3.29 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.mp4 3.29 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.mp4 3.29 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.mp4 3.29 MB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.mp4 3.28 MB
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.mp4 3.28 MB
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.mp4 3.27 MB
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.mp4 3.27 MB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.mp4 3.26 MB
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.mp4 3.26 MB
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.mp4 3.25 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.mp4 3.25 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.mp4 3.24 MB
Part 16-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.mp4 3.24 MB
Part 07-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.mp4 3.24 MB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.mp4 3.24 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.mp4 3.23 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.mp4 3.23 MB
Part 16-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.mp4 3.23 MB
Part 04-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.mp4 3.21 MB
Part 16-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.mp4 3.21 MB
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.mp4 3.19 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/19. Order By Part II-XQCjREdOqwE.mp4 3.18 MB
Part 03-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.mp4 3.18 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.mp4 3.18 MB
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.mp4 3.17 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.mp4 3.17 MB
Part 16-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.mp4 3.17 MB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.mp4 3.16 MB
Part 08-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.mp4 3.15 MB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.mp4 3.15 MB
Part 15-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.mp4 3.15 MB
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.mp4 3.15 MB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.mp4 3.14 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.mp4 3.13 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Continue Crawl Solution-cFwJ_MO3ofs.mp4 3.13 MB
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.mp4 3.13 MB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.mp4 3.12 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.mp4 3.11 MB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.mp4 3.11 MB
Part 18-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.mp4 3.11 MB
Part 16-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.mp4 3.1 MB
Part 03-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.mp4 3.09 MB
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.mp4 3.09 MB
Part 16-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.mp4 3.08 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.mp4 3.08 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/06. Types Of Errors - Part I-aw6GMxIvENc.mp4 3.07 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.mp4 3.07 MB
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.mp4 3.06 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.mp4 3.06 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.mp4 3.06 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/19. Congratulations!-_FPpbuuW-1o.mp4 3.05 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.mp4 3.04 MB
Part 04-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.mp4 3.04 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.mp4 3.03 MB
Part 12-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.mp4 3.03 MB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Instructor Introduction Charlie And Phillip-8ar0mETDrZw.mp4 3.03 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.mp4 3.01 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.mp4 3 MB
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.mp4 3 MB
Part 15-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.mp4 2.99 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.mp4 2.98 MB
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.mp4 2.98 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.mp4 2.97 MB
Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.mp4 2.96 MB
Part 11-Module 01-Lesson 02_Create A Git Repo/05. Create A Repo - Outro-h7j4STDFCjs.mp4 2.96 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.mp4 2.95 MB
Part 08-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.mp4 2.95 MB
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.mp4 2.95 MB
Part 07-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.mp4 2.94 MB
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.mp4 2.94 MB
Part 04-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.mp4 2.94 MB
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.mp4 2.92 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.mp4 2.91 MB
Part 04-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.mp4 2.91 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.mp4 2.91 MB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.mp4 2.9 MB
Part 02-Module 01-Lesson 03_Data Structures and Loops/01. Ud1110 IntroPy L301 Welcome To Lesson 3-ikOWhrOUgLc.mp4 2.9 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.mp4 2.9 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.mp4 2.9 MB
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.mp4 2.89 MB
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.mp4 2.89 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.mp4 2.89 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.mp4 2.88 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.mp4 2.88 MB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.mp4 2.87 MB
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.mp4 2.85 MB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. INTRODUÇÃO AO PROJETO PRINCIPAL V2---9IFCNBM6Y.mp4 2.85 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.mp4 2.85 MB
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.mp4 2.85 MB
Part 18-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.mp4 2.84 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.mp4 2.83 MB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.mp4 2.83 MB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.mp4 2.83 MB
Part 16-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.mp4 2.83 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.mp4 2.83 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.mp4 2.82 MB
Part 07-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.mp4 2.82 MB
Part 16-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.mp4 2.82 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.mp4 2.81 MB
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.mp4 2.81 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.mp4 2.81 MB
Part 15-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.mp4 2.81 MB
Part 04-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.mp4 2.81 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.mp4 2.81 MB
Part 08-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.mp4 2.8 MB
Part 07-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.mp4 2.8 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.mp4 2.8 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.mp4 2.8 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.mp4 2.79 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.mp4 2.79 MB
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.mp4 2.79 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.mp4 2.79 MB
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.mp4 2.79 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.mp4 2.78 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.mp4 2.78 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.mp4 2.78 MB
Part 15-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.mp4 2.78 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.mp4 2.78 MB
Part 12-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.mp4 2.77 MB
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.mp4 2.77 MB
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.mp4 2.76 MB
Part 11-Module 01-Lesson 01_What is Version Control/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 11 Google Docs Revision History Walkthrough-GcvvbdKEchk.mp4 2.76 MB
Part 07-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.mp4 2.76 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.mp4 2.75 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.mp4 2.75 MB
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.mp4 2.75 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.mp4 2.75 MB
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.mp4 2.74 MB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.mp4 2.74 MB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.mp4 2.73 MB
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.mp4 2.71 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.mp4 2.7 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.mp4 2.7 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.mp4 2.7 MB
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.mp4 2.69 MB
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.mp4 2.68 MB
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.mp4 2.68 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.mp4 2.68 MB
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.mp4 2.68 MB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.mp4 2.67 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.mp4 2.67 MB
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.mp4 2.67 MB
Part 11-Module 01-Lesson 06_Undoing Changes/06. Course Outro-twn_cheqoK8.mp4 2.67 MB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/01. Welcome To DAND Term 2-OOcC8OUJmc0.mp4 2.67 MB
Part 16-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.mp4 2.66 MB
Part 16-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.mp4 2.66 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.mp4 2.65 MB
Part 09-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.mp4 2.64 MB
Part 16-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.mp4 2.64 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-aUc0FKD4834.mp4 2.64 MB
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.mp4 2.63 MB
Part 16-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.mp4 2.63 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.mp4 2.62 MB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.mp4 2.61 MB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.mp4 2.61 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.mp4 2.61 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.mp4 2.61 MB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 15 Git The Big Picture-dVil8e0yptQ.mp4 2.6 MB
Part 11-Module 01-Lesson 06_Undoing Changes/05. Undoing Changes--_PPVk2UZMU.mp4 2.59 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.mp4 2.59 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/08. Self JOINs-tw_VzEGBOvI.mp4 2.58 MB
Part 16-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.mp4 2.58 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.mp4 2.57 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.mp4 2.57 MB
Part 04-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.mp4 2.57 MB
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.mp4 2.56 MB
Part 18-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.mp4 2.55 MB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.mp4 2.55 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.mp4 2.55 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.mp4 2.54 MB
Part 18-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.mp4 2.54 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.mp4 2.54 MB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.mp4 2.52 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.mp4 2.52 MB
Part 15-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.mp4 2.52 MB
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.mp4 2.52 MB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.mp4 2.52 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.mp4 2.51 MB
Part 16-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.mp4 2.51 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.mp4 2.5 MB
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.mp4 2.5 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.mp4 2.5 MB
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.mp4 2.49 MB
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.mp4 2.49 MB
Part 04-Module 01-Lesson 12_Hypothesis Testing/13. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.mp4 2.48 MB
Part 16-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.mp4 2.48 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function-XUZIGbX3JIg.mp4 2.48 MB
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.mp4 2.47 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.mp4 2.47 MB
Part 15-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.mp4 2.47 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/16. ORDER BY Statement-wqj2As31LqI.mp4 2.46 MB
Part 03-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.mp4 2.46 MB
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.mp4 2.46 MB
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.mp4 2.46 MB
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.mp4 2.45 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.mp4 2.43 MB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/02. Projects Term 1 V2-1e1y6QB34YM.mp4 2.42 MB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/01. Introduction-2Y279421n3A.mp4 2.42 MB
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.mp4 2.41 MB
Part 16-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.mp4 2.41 MB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.mp4 2.4 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.mp4 2.39 MB
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.mp4 2.39 MB
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.mp4 2.39 MB
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.mp4 2.38 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.mp4 2.38 MB
Part 09-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.mp4 2.37 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.mp4 2.37 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/41. AND BETWEEN Operators-nBuDPneWcKY.mp4 2.37 MB
Part 03-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.mp4 2.37 MB
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.mp4 2.36 MB
Part 08-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.mp4 2.36 MB
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.mp4 2.36 MB
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.mp4 2.35 MB
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.mp4 2.35 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.mp4 2.34 MB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.mp4 2.34 MB
Part 16-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.mp4 2.34 MB
Part 15-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.mp4 2.32 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.mp4 2.31 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-e_8DmUBHAao.mp4 2.31 MB
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.mp4 2.31 MB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.mp4 2.29 MB
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.mp4 2.29 MB
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.mp4 2.29 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.mp4 2.29 MB
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.mp4 2.29 MB
Part 16-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.mp4 2.28 MB
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.mp4 2.28 MB
Part 16-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.mp4 2.27 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.mp4 2.27 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.mp4 2.26 MB
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.mp4 2.26 MB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.mp4 2.26 MB
Part 12-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.mp4 2.25 MB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.mp4 2.25 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.mp4 2.25 MB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.mp4 2.24 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.mp4 2.24 MB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.mp4 2.23 MB
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.mp4 2.23 MB
Part 07-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.mp4 2.22 MB
Part 11-Module 01-Lesson 03_Review a Repo's History/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 11 Git Log Output Explained-xJfurQcVYfo.mp4 2.22 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.mp4 2.21 MB
Part 04-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.mp4 2.21 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.mp4 2.19 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.mp4 2.19 MB
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.mp4 2.19 MB
Part 16-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.mp4 2.17 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/32. LIKE Operator-O5z6eWkNip4.mp4 2.17 MB
Part 03-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.mp4 2.17 MB
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.mp4 2.17 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.mp4 2.17 MB
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.mp4 2.17 MB
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.mp4 2.16 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.mp4 2.16 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.mp4 2.16 MB
Part 04-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.mp4 2.16 MB
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.mp4 2.15 MB
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.mp4 2.15 MB
Part 08-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.mp4 2.14 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.mp4 2.14 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.mp4 2.14 MB
Part 15-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.mp4 2.14 MB
Part 04-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.mp4 2.13 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.mp4 2.13 MB
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.mp4 2.13 MB
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.mp4 2.13 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.mp4 2.13 MB
Part 03-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.mp4 2.12 MB
Part 03-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.mp4 2.12 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/25. WHERE with Non-Numeric Data-_pLx7MHOyjo.mp4 2.12 MB
Part 07-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.mp4 2.12 MB
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.mp4 2.12 MB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.mp4 2.11 MB
Part 04-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.mp4 2.1 MB
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.mp4 2.1 MB
Part 11-Module 01-Lesson 06_Undoing Changes/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L6 17 Soft Vs Medium Vs Hard Walkthrough-UN7ki2G2yKc.mp4 2.1 MB
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.mp4 2.1 MB
Part 07-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.mp4 2.09 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.mp4 2.09 MB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/01. Ud1110 IntroPy L201 Welcome Back!-oCCMSsCc4Iw.mp4 2.09 MB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.mp4 2.08 MB
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.mp4 2.08 MB
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.mp4 2.08 MB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.mp4 2.07 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.mp4 2.07 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.mp4 2.07 MB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.mp4 2.06 MB
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.mp4 2.06 MB
Part 04-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.mp4 2.05 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.mp4 2.05 MB
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.mp4 2.04 MB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.mp4 2.03 MB
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.mp4 2.03 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.mp4 2.03 MB
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.mp4 2.03 MB
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.mp4 2.03 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Businesses Choose Databases-j4ey7--h9r8.mp4 2.03 MB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.mp4 2.03 MB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.mp4 2.03 MB
Part 16-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.mp4 2.01 MB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.mp4 2.01 MB
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.mp4 2.01 MB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-add-to-staging-recap.gif 2 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.mp4 2 MB
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.mp4 1.99 MB
Part 16-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.mp4 1.98 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.mp4 1.96 MB
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.mp4 1.96 MB
Part 03-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.mp4 1.94 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/44. OR Operator-3vLGEuXAAvA.mp4 1.94 MB
Part 08-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.mp4 1.94 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-b7oUjvNJWCc.mp4 1.94 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.mp4 1.93 MB
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.mp4 1.93 MB
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.mp4 1.92 MB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.mp4 1.91 MB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.mp4 1.91 MB
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.mp4 1.91 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/38. NOT Operator-dSQF87oW8a0.mp4 1.9 MB
Part 03-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.mp4 1.9 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.mp4 1.9 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.mp4 1.89 MB
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.mp4 1.89 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.mp4 1.88 MB
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.mp4 1.88 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.mp4 1.88 MB
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.mp4 1.88 MB
Part 07-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.mp4 1.87 MB
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.mp4 1.86 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.mp4 1.86 MB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 25 Git Log Vs Git Log --Oneline Walkthru-rn6v_QgYFnU.mp4 1.85 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.mp4 1.85 MB
Part 07-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.mp4 1.84 MB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.mp4 1.84 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price-Ck4i1Yk4pT0.mp4 1.83 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.mp4 1.82 MB
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.mp4 1.82 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 3-oVGmi4zBOT8.mp4 1.82 MB
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.mp4 1.81 MB
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.mp4 1.81 MB
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.mp4 1.81 MB
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.mp4 1.8 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.mp4 1.8 MB
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.mp4 1.8 MB
Part 08-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.mp4 1.79 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.mp4 1.79 MB
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.mp4 1.79 MB
Part 16-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.mp4 1.79 MB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.mp4 1.79 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.mp4 1.78 MB
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.mp4 1.77 MB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/img/wave.gif 1.76 MB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/img/wave.gif 1.76 MB
Part 03-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.mp4 1.76 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/35. IN Operator-_JPO7wwX3uA.mp4 1.76 MB
Part 16-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.mp4 1.75 MB
Part 15-Module 02-Lesson 05_Trees/13. BST Complications-pcB0wV7myy4.mp4 1.75 MB
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.mp4 1.75 MB
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.mp4 1.74 MB
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.mp4 1.74 MB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.mp4 1.74 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.mp4 1.73 MB
Part 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.mp4 1.72 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/44. OR Statement-DRmkKVhe6-s.mp4 1.7 MB
Part 03-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.mp4 1.7 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.mp4 1.69 MB
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.mp4 1.69 MB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.mp4 1.69 MB
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.mp4 1.69 MB
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.mp4 1.69 MB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.mp4 1.69 MB
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.mp4 1.68 MB
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.mp4 1.68 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.mp4 1.68 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.mp4 1.68 MB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.mp4 1.67 MB
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.mp4 1.67 MB
Part 04-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.mp4 1.65 MB
Part 03-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.mp4 1.65 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/28. Arithmetic Operators-fgcJdiNECxI.mp4 1.65 MB
Part 08-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.mp4 1.64 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.mp4 1.64 MB
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.mp4 1.64 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.mp4 1.63 MB
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.mp4 1.62 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.mp4 1.62 MB
Part 04-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.mp4 1.61 MB
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.mp4 1.61 MB
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.mp4 1.61 MB
Part 11-Module 01-Lesson 03_Review a Repo's History/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 33 Git Log Vs Git Log --Stat Walkthru-aOICKP_9xiY.mp4 1.61 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.mp4 1.6 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.mp4 1.6 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.mp4 1.6 MB
Part 12-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.mp4 1.59 MB
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.mp4 1.59 MB
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.mp4 1.59 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.mp4 1.59 MB
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.mp4 1.58 MB
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.mp4 1.58 MB
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.mp4 1.58 MB
Part 07-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.mp4 1.57 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.mp4 1.57 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.mp4 1.57 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.mp4 1.55 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.mp4 1.55 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.mp4 1.55 MB
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.mp4 1.53 MB
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.mp4 1.51 MB
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.mp4 1.51 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.mp4 1.51 MB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.mp4 1.51 MB
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.mp4 1.5 MB
Part 16-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.mp4 1.5 MB
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.mp4 1.49 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.mp4 1.49 MB
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.mp4 1.49 MB
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.mp4 1.49 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.mp4 1.49 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.mp4 1.49 MB
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.mp4 1.48 MB
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.mp4 1.48 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.mp4 1.48 MB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.mp4 1.47 MB
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.mp4 1.46 MB
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.mp4 1.46 MB
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.mp4 1.45 MB
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.mp4 1.44 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.mp4 1.44 MB
Part 07-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.mp4 1.43 MB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 71 Merging-gQiWicrreJg.mp4 1.43 MB
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.mp4 1.43 MB
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.mp4 1.42 MB
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.mp4 1.42 MB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.mp4 1.41 MB
Part 02-Module 01-Lesson 01_Numbers and Strings/02. Ud1110 IntroPy L1 07 Arithmetic Expression In Python-Iq3ovQqBj1M.mp4 1.41 MB
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.mp4 1.4 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.mp4 1.4 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-UnkrtPPx9-c.mp4 1.4 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.mp4 1.39 MB
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.mp4 1.39 MB
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.mp4 1.39 MB
Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.mp4 1.38 MB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 1-APRpwqFpGwI.mp4 1.38 MB
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.mp4 1.37 MB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Coding inside the skeleton loop-MRPdqOwnqag.mp4 1.36 MB
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.mp4 1.35 MB
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.mp4 1.34 MB
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.mp4 1.33 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.mp4 1.33 MB
Part 04-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.mp4 1.33 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price-MZyle39D5Ks.mp4 1.32 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/04. Entity Relationship Diagrams-YY2TAJLEINA.mp4 1.31 MB
Part 03-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.mp4 1.31 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.mp4 1.31 MB
Part 16-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.mp4 1.31 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.mp4 1.3 MB
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.mp4 1.3 MB
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.mp4 1.3 MB
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.mp4 1.29 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.mp4 1.29 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.mp4 1.29 MB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.mp4 1.29 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.mp4 1.28 MB
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.mp4 1.28 MB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.mp4 1.27 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.mp4 1.27 MB
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.mp4 1.26 MB
Part 03-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.mp4 1.25 MB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/06. How Databases Store Data-H0C9z_sRvLE.mp4 1.24 MB
Part 08-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.mp4 1.24 MB
Part 03-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.mp4 1.24 MB
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.mp4 1.24 MB
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.mp4 1.23 MB
Part 08-Module 05-Lesson 01_Wrangle and Analyze Data/img/dogtionary-combined.png 1.23 MB
Part 16-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.mp4 1.22 MB
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.mp4 1.22 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.mp4 1.21 MB
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.mp4 1.21 MB
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.mp4 1.21 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.mp4 1.21 MB
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.mp4 1.21 MB
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.mp4 1.21 MB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 15-Module 02-Lesson 08_Technical Interview - Python/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 13-Module 01-Lesson 03_Udacity Professional Profile/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 12-Module 01-Lesson 01_GitHub Review/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 14-Module 01-Lesson 01_Conduct a Job Search/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 15-Module 01-Lesson 05_Interview Practice/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 13-Module 01-Lesson 02_LinkedIn Review/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.mp4 1.19 MB
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.mp4 1.19 MB
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.mp4 1.18 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.mp4 1.18 MB
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.mp4 1.17 MB
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.mp4 1.17 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.mp4 1.17 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.mp4 1.17 MB
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.mp4 1.17 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price--P5lMGuVA6U.mp4 1.16 MB
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.mp4 1.16 MB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.mp4 1.16 MB
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.mp4 1.16 MB
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.mp4 1.15 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.mp4 1.14 MB
Part 14-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.mp4 1.14 MB
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.mp4 1.14 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.mp4 1.13 MB
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.mp4 1.13 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.mp4 1.12 MB
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.mp4 1.12 MB
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.mp4 1.12 MB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/12. Ud1110 IntroPy L237 Break Up Your Code Ideas-qrp8r48BPUs.mp4 1.11 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.mp4 1.11 MB
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.mp4 1.1 MB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.mp4 1.1 MB
Part 03-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.mp4 1.09 MB
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.mp4 1.08 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.mp4 1.08 MB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/05. Introduction-fxNSn63xFvA.mp4 1.08 MB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/06. Introduction-fxNSn63xFvA.mp4 1.08 MB
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.mp4 1.07 MB
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-r5qca6q4Fn4.mp4 1.07 MB
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.mp4 1.07 MB
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.mp4 1.06 MB
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.mp4 1.06 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.mp4 1.06 MB
Part 03-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.mp4 1.06 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.mp4 1.06 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.mp4 1.06 MB
Part 04-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.mp4 1.06 MB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 03 Tagging Overview-D4VdXT72ASE.mp4 1.06 MB
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.mp4 1.05 MB
Part 16-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.mp4 1.04 MB
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.mp4 1.04 MB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.mp4 1.04 MB
Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.mp4 1.04 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.mp4 1.04 MB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/screenshot-2018-01-15-17.36.32.png 1.03 MB
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.mp4 1.03 MB
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.mp4 1.03 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.mp4 1.03 MB
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.mp4 1.01 MB
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.mp4 1.01 MB
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.mp4 1021.89 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.mp4 1016.04 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/img/48713571.gif 1011.65 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price--9CHGW25yMg.mp4 1010.76 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.mp4 1009.81 KB
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.mp4 996.8 KB
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.mp4 991.73 KB
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.mp4 990.87 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/img/inner-outer.png 989.08 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/oblstsm-imgur.gif 988.07 KB
Part 16-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.mp4 985.36 KB
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.mp4 978.72 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.mp4 975.66 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.mp4 975.6 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.mp4 975.39 KB
Part 11-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-course-git-blog-project-in-browser.png 968.54 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/img/left-right.png 964.43 KB
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.mp4 960.33 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.mp4 954.56 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2017-12-07-at-3.48.20-pm.png 925.38 KB
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.mp4 920.84 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.mp4 918.81 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.mp4 918.37 KB
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.mp4 918.37 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.mp4 915.12 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 17 Git The Big Picture 2-rFtUkk-sCqw.mp4 908.99 KB
Part 08-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.mp4 897.42 KB
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.mp4 896.74 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.mp4 893.3 KB
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.mp4 891.26 KB
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.mp4 886.38 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.mp4 886.38 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/img/screen-shot-2017-11-07-at-2.17.08-pm.png 882.6 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. Projects-1-E_ZYovKeI.mp4 867.3 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.mp4 863.99 KB
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.mp4 863.33 KB
Part 16-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.mp4 853.58 KB
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.mp4 842.63 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.mp4 836.26 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.mp4 832.68 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/img/screen-shot-2017-11-07-at-2.18.27-pm.png 832.02 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.mp4 831.76 KB
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.mp4 828.32 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 2-so5zydnbYEg.mp4 825.59 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.mp4 824.92 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.mp4 817.42 KB
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.mp4 817.3 KB
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.mp4 805.43 KB
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.mp4 803.69 KB
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.mp4 803.67 KB
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.mp4 800.53 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/img/3011778732.gif 798.3 KB
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.mp4 797.83 KB
Part 01-Module 02-Lesson 02_Explore Weather Trends/img/earth.png 795.63 KB
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.mp4 792.74 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.mp4 792.74 KB
Part 08-Module 05-Lesson 01_Wrangle and Analyze Data/img/screenshot-2017-10-10-18.43.41.png 788.76 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.mp4 787.82 KB
Part 04-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.mp4 787.82 KB
Part 16-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.mp4 782.02 KB
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.mp4 780.78 KB
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.mp4 776.82 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.mp4 774.95 KB
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.mp4 774.95 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.mp4 771.83 KB
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.mp4 770.56 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.mp4 770.56 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/img/3013458575.gif 766.43 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/img/3017968763.gif 765.91 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.mp4 765.63 KB
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.mp4 765.63 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/groups-used-in-map.png 759.23 KB
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.mp4 757.48 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/img/get-hired-with-the-udacity-career-portal.gif 756.73 KB
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.mp4 754.47 KB
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.mp4 753.05 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.mp4 751.89 KB
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.mp4 747.61 KB
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.mp4 747.17 KB
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.mp4 745.32 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.mp4 743.92 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/img/3013038717.gif 741.74 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/img/3029558686.gif 738.48 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/img/3046518548.gif 736.99 KB
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.mp4 736.69 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.mp4 735.16 KB
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.mp4 734.96 KB
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.mp4 734.83 KB
Part 07-Module 01-Lesson 02_R Basics/img/805108698.gif 732.66 KB
Part 16-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.mp4 726.61 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.mp4 720.53 KB
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.mp4 720.53 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.mp4 719.39 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.mp4 715.26 KB
Part 12-Module 01-Lesson 01_GitHub Review/img/6509638772.gif 711.08 KB
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.mp4 707.99 KB
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.mp4 702.49 KB
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.mp4 701.34 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/img/3007818802.gif 696.79 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.mp4 693.68 KB
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.mp4 693.35 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/img/3000408954.gif 682.95 KB
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.mp4 682.36 KB
Part 08-Module 05-Lesson 01_Wrangle and Analyze Data/img/dog-pred.png 680.02 KB
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.mp4 677.09 KB
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.mp4 676.1 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/img/3003048586.gif 675.79 KB
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.mp4 675.14 KB
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.mp4 672.32 KB
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.mp4 672.27 KB
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.mp4 671.97 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/img/866348580.gif 671.32 KB
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.mp4 668.73 KB
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Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.mp4 467.38 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/img/3061308637.gif 173.82 KB
Part 16-Module 01-Lesson 11_Text Learning/img/3002338759.gif 173.61 KB
Part 16-Module 01-Lesson 09_Clustering/img/3034378634.gif 173.12 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/hierarchy-categories-labeled.png 172.36 KB
Part 16-Module 01-Lesson 12_Feature Selection/img/3049908569.gif 171.64 KB
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Part 04-Module 01-Lesson 12_Hypothesis Testing/img/screen-shot-2018-01-24-at-12.03.45-am.png 170.85 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/dual-axis-before.png 170.61 KB
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/img/874499235.gif 170.5 KB
Part 16-Module 01-Lesson 14_Validation/img/3053458603.gif 170 KB
Part 07-Module 01-Lesson 03_Explore One Variable/img/834268560.gif 169.95 KB
Part 16-Module 01-Lesson 14_Validation/img/2980648814.gif 169.5 KB
Part 16-Module 01-Lesson 02_Naive Bayes/img/3012238654.gif 169.26 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/media/command+palette.mp4 169.16 KB
Part 02-Module 02-Lesson 01_Python Project/media/command+palette.mp4 169.16 KB
Part 07-Module 01-Lesson 03_Explore One Variable/img/805459084.gif 168.95 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/capture1.png 168.59 KB
Part 16-Module 01-Lesson 03_SVM/img/3029308691.gif 168.16 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/img/880468669.gif 167.88 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-status.png 167.54 KB
Part 16-Module 01-Lesson 07_Regressions/img/3020778551.gif 165.56 KB
Part 16-Module 01-Lesson 12_Feature Selection/img/3003368625.gif 165.25 KB
Part 16-Module 01-Lesson 09_Clustering/img/3004978616.gif 164.57 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-changes-add-color.png 164.17 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/img/screen-shot-2017-09-13-at-4.06.33-pm.png 163.55 KB
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Part 16-Module 01-Lesson 14_Validation/img/3043408576.gif 162.91 KB
Part 16-Module 01-Lesson 08_Outliers/img/2947738692.gif 162.01 KB
Part 16-Module 01-Lesson 03_SVM/img/3027138551.gif 162 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/new-sheets.png 161.67 KB
Part 16-Module 01-Lesson 12_Feature Selection/img/3002978730.gif 160.98 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/filter-interactive-menu.png 160 KB
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/img/867888969.gif 159.84 KB
Part 16-Module 01-Lesson 13_PCA/img/3059228570.gif 159.84 KB
Part 16-Module 01-Lesson 07_Regressions/img/3014338742.gif 159.42 KB
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Part 02-Module 02-Lesson 01_Python Project/img/magic-timeit.png 157.29 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/img/magic-timeit.png 157.29 KB
Part 16-Module 01-Lesson 10_Feature Scaling/img/3076888537.gif 156.58 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/img/server-shutdown.png 155.42 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/filter-interactive-changed.png 155.38 KB
Part 11-Module 01-Lesson 06_Undoing Changes/img/ud123-l6-git-revert-prep.png 155.04 KB
Part 09-Module 01-Lesson 02_Design/img/challenger2.gif 154.59 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-checkout-sidebar.png 154.24 KB
Part 16-Module 01-Lesson 13_PCA/img/3062928590.gif 152.82 KB
Part 07-Module 01-Lesson 03_Explore One Variable/img/805609565.gif 152.8 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/img/new-dashboard-button.png 152.75 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/small-multiples-with-category.png 152.04 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/screenshot-2017-09-25-21.03.17.png 151.91 KB
Part 07-Module 01-Lesson 01_What is EDA/img/826879024.gif 151.82 KB
Part 07-Module 01-Lesson 03_Explore One Variable/img/809989248.gif 151.65 KB
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Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/screen-shot-2017-09-07-at-10.27.16-am.png 150.76 KB
Part 03-Module 02-Lesson 04_Programming Workflow for Data Analysis/img/script-plot.png 149.54 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-branch-sidebar.png 149.38 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/hierarchy-continuous.png 149.14 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/screen-shot-2017-09-07-at-10.27.02-am.png 149.03 KB
Part 16-Module 01-Lesson 09_Clustering/img/3019118758.gif 148.85 KB
Part 16-Module 01-Lesson 09_Clustering/img/3040398570.gif 148.74 KB
Part 16-Module 01-Lesson 11_Text Learning/img/3004028719.gif 148.73 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/img/3053448554.gif 148.49 KB
Part 11-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-git-clone.gif 147.36 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/dual-axis-dragged-cropped.png 147.33 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/filter-from-view.png 146.04 KB
Part 16-Module 01-Lesson 03_SVM/img/2941178604.gif 145.92 KB
Part 07-Module 01-Lesson 03_Explore One Variable/img/828308621.gif 144.95 KB
Part 07-Module 01-Lesson 02_R Basics/img/811719066.gif 144.42 KB
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Part 16-Module 01-Lesson 07_Regressions/img/3003308650.gif 143.39 KB
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Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature.html 141.31 KB
Part 09-Module 02-Lesson 01_Create a Tableau Story/img/madewithudacity-twitter.png 141.21 KB
Part 16-Module 01-Lesson 07_Regressions/img/2978908558.gif 140.37 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/img/cover-letter-body-good.png 140.03 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-tag.png 139.67 KB
Part 16-Module 01-Lesson 04_Decision Trees/img/3026088745.gif 139.32 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/img/869958633.gif 138.33 KB
Part 16-Module 01-Lesson 03_SVM/img/2945548572.gif 138.02 KB
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Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/show-me-selected.png 137.22 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/img/873369305.gif 137.13 KB
Part 16-Module 01-Lesson 03_SVM/img/2969508540.gif 136.54 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/hierarchy-month.png 136.2 KB
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Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/show-me-bar-chart.png 133.94 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/img/l1-diagrams.002.jpeg 133.85 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/small-multiples-quarters.png 133.83 KB
Part 08-Module 04-Lesson 01_Cleaning Data/img/screenshot-2017-10-10-23.31.14.png 133.69 KB
Part 08-Module 04-Lesson 01_Cleaning Data/img/screenshot-2017-10-10-23.10.49.png 133.35 KB
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Part 16-Module 01-Lesson 03_SVM/img/3010678612.gif 132.67 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/screen-shot-2017-09-12-at-7.23.27-pm.png 131.94 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/img/863168719.gif 131.75 KB
Part 16-Module 01-Lesson 04_Decision Trees/img/3019888682.gif 131.69 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/order-date-hierarchy.png 130.98 KB
Part 03-Module 02-Lesson 04_Programming Workflow for Data Analysis/img/ipython-a4.png 130.73 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/img/3039308629.gif 130.58 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/screenshot-2017-09-24-13.44.50.png 130.55 KB
Part 16-Module 01-Lesson 11_Text Learning/img/3014438788.gif 130.37 KB
Part 16-Module 01-Lesson 10_Feature Scaling/img/3007478963.gif 130.31 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/img/weekly-sales.png 129.83 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/colors-choose-palette.png 129.27 KB
Part 16-Module 01-Lesson 08_Outliers/img/2968538614.gif 129.16 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/img/3008128667.gif 128.51 KB
Part 16-Module 01-Lesson 02_Naive Bayes/img/3010848726.gif 128.13 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/img/3003988627.gif 126.74 KB
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Part 11-Module 01-Lesson 06_Undoing Changes/img/ud123-l6-git-revert-mixed.png 125.86 KB
Part 16-Module 01-Lesson 03_SVM/img/2972018562.gif 125.64 KB
Part 16-Module 01-Lesson 08_Outliers/img/2949658626.gif 125.24 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/img/3028928653.gif 125.04 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-log-pre-tag.png 124.69 KB
Part 16-Module 01-Lesson 09_Clustering/img/3058428551.gif 124.68 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/img/natgeo-scatter.jpg 123.75 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/img/3023678711.gif 123.31 KB
Part 16-Module 01-Lesson 04_Decision Trees/img/3005018665.gif 123.19 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/groups-create-hover.png 122.94 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/img/3016218654.gif 122.51 KB
Part 03-Module 02-Lesson 04_Programming Workflow for Data Analysis/img/script-columns-functions.png 122.2 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/img/3030708562.gif 121.77 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/sorted-markets-with-arrow.png 121.62 KB
Part 08-Module 05-Lesson 01_Wrangle and Analyze Data/img/screenshot-2017-10-28-00.29.25.png 120.66 KB
Part 16-Module 01-Lesson 07_Regressions/img/2963708620.gif 120.46 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/view-data-with-arrow.png 120.4 KB
Part 16-Module 01-Lesson 02_Naive Bayes/img/3006318739.gif 120.35 KB
Part 04-Module 01-Lesson 07_Bayes Rule/img/screen-shot-2017-08-02-at-11.49.10-am.png 120.26 KB
Part 07-Module 01-Lesson 03_Explore One Variable/img/814098604.gif 119.19 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/market-granularity.png 118.55 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/rename-columns.png 117.85 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/img/7day-moving-average.png 116.69 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/split-string-column.png 116.53 KB
Part 03-Module 03-Lesson 02_SQL Joins/img/screen-shot-2017-08-10-at-8.23.48-pm.png 115.1 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/market-number-of-records.png 114.72 KB
Part 11-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-base-directory-git-repo.png 113.61 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/screen-shot-2017-09-12-at-1.45.29-pm.png 111.89 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/market-to-columns-arrow.png 111.83 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-commit-terminal-hangs.png 111 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-new-git-project.png 110.42 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/img/ud123-l3-git-log-p.png 110.08 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/img/conda-tab.png 109.92 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/img/866638906.gif 109.62 KB
Part 03-Module 02-Lesson 04_Programming Workflow for Data Analysis/img/script-columns-simple.png 108.71 KB
Part 04-Module 01-Lesson 07_Bayes Rule/img/screen-shot-2017-08-02-at-11.40.37-am.png 108.23 KB
Part 11-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-new-git-project.png 106.52 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/img/763288677.gif 105.46 KB
Part 09-Module 01-Lesson 02_Design/img/apple.jpg 105.41 KB
Part 03-Module 03-Lesson 02_SQL Joins/img/screen-shot-2017-08-14-at-4.10.54-pm.png 105.31 KB
Part 03-Module 03-Lesson 02_SQL Joins/img/screen-shot-2017-08-14-at-4.04.44-pm.png 103.54 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/img/notebook-server.png 103.33 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/img/758558730.gif 102.93 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/img/761138624.gif 102.59 KB
Part 02-Module 02-Lesson 01_Python Project/img/new-notebook.png 101.77 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/img/new-notebook.png 101.77 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/img/story-interface.png 101.71 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/img/screen-shot-2017-08-28-at-4.28.43-pm.png 101.56 KB
Part 07-Module 01-Lesson 01_What is EDA/img/862788887.gif 100.66 KB
Part 07-Module 01-Lesson 02_R Basics/img/830829287.gif 100.47 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/img/697369978.gif 99.89 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/img/762298675.gif 99.3 KB
Part 16-Module 01-Lesson 11_Text Learning/img/3057419003.gif 98.45 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/img/screen-shot-2018-08-15-at-9.45.12-am.png 97.34 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/img/screen-shot-2018-08-15-at-9.45.12-am.png 97.34 KB
Part 03-Module 01-Lesson 01_Anaconda/media/conda_enter.mp4 97.26 KB
Part 04-Module 01-Lesson 06_Conditional Probability/img/48271967.gif 96.13 KB
Part 11-Module 01-Lesson 06_Undoing Changes/img/ud123-l6-git-revert-soft.png 95.84 KB
Part 08-Module 02-Lesson 01_Gathering Data/img/screenshot-2017-09-26-10.24.41.png 95.68 KB
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Part 03-Module 01-Lesson 02_Jupyter Notebooks/img/notebook-json.png 95.29 KB
Part 11-Module 01-Lesson 06_Undoing Changes/img/ud123-l6-git-revert-hard.png 95.16 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/img/screen-shot-2018-10-03-at-2.27.15-pm.png 95.13 KB
Part 13-Module 01-Lesson 02_LinkedIn Review/media/unnamed-project-desc-0.gif 94.58 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/filter-show.png 94.16 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/img/screen-shot-2017-08-23-at-3.39.03-pm.png 93.78 KB
Part 08-Module 03-Lesson 01_Assessing Data/img/screenshot-2017-10-10-02.10.18.png 93.73 KB
Part 11-Module 01-Lesson 01_What is Version Control/img/ud123-l1-terminal-config-windows.png 93.23 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/img/48728202.gif 92.14 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/img/48684686.gif 91.62 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/img/48698526.gif 90.98 KB
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Part 08-Module 02-Lesson 01_Gathering Data/img/screenshot-2017-09-26-10.20.14.png 90.86 KB
Part 04-Module 01-Lesson 06_Conditional Probability/img/48734324.gif 90.86 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/img/magic-matplotlib.png 90.72 KB
Part 02-Module 02-Lesson 01_Python Project/img/magic-matplotlib.png 90.72 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/img/48721292.gif 90.54 KB
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Part 04-Module 01-Lesson 03_Admissions Case Study/img/48698525.gif 89.16 KB
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Part 07-Module 01-Lesson 02_R Basics/img/875339076.gif 87.85 KB
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Part 04-Module 01-Lesson 15_Multiple Linear Regression/img/resid2.jpg 87.09 KB
Part 04-Module 01-Lesson 07_Bayes Rule/img/48743074.gif 87.07 KB
Part 04-Module 01-Lesson 06_Conditional Probability/img/48271966.gif 86.74 KB
Part 04-Module 01-Lesson 07_Bayes Rule/img/48480561.gif 85.92 KB
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Part 04-Module 01-Lesson 06_Conditional Probability/img/48716290.gif 84.79 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/img/inner-join.png 84.77 KB
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Part 04-Module 01-Lesson 04_Probability/img/48667978.gif 84.52 KB
Part 04-Module 01-Lesson 07_Bayes Rule/img/screen-shot-2017-08-02-at-4.57.01-pm.png 84 KB
Part 04-Module 01-Lesson 06_Conditional Probability/img/48739228.gif 83.99 KB
Part 04-Module 01-Lesson 07_Bayes Rule/img/48646780.gif 83.92 KB
Part 04-Module 01-Lesson 07_Bayes Rule/img/48445276.gif 83.24 KB
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Part 04-Module 01-Lesson 06_Conditional Probability/img/48641639.gif 83.13 KB
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Part 11-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-base-directory.png 82.6 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/img/5.dap-quiz-img2.png 82.6 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/img/48688787.gif 82.4 KB
Part 04-Module 01-Lesson 04_Probability/img/48752009.gif 82.38 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/img/48741083.gif 82.16 KB
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Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/dual-axis-menu.png 81.85 KB
Part 03-Module 01-Lesson 01_Anaconda/img/conda-install.png 81.15 KB
Part 03-Module 03-Lesson 02_SQL Joins/img/screen-shot-2017-08-14-at-1.12.55-pm.png 81.01 KB
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Part 16-Module 01-Lesson 07_Regressions/img/3072338540.gif 80.48 KB
Part 03-Module 03-Lesson 02_SQL Joins/img/erd.png 80.34 KB
Part 03-Module 03-Lesson 01_Basic SQL/img/screen-shot-2017-10-19-at-5.33.45-pm.png 80.34 KB
Part 04-Module 01-Lesson 07_Bayes Rule/img/48311831.gif 80.33 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/img/48658976.gif 80.19 KB
Part 04-Module 01-Lesson 06_Conditional Probability/img/48632848.gif 79.8 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/img/notebook-download.png 79.54 KB
Part 02-Module 02-Lesson 01_Python Project/img/notebook-download.png 79.54 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/img/screen-shot-2017-08-02-at-11.14.25-am.png 79.36 KB
Part 03-Module 03-Lesson 01_Basic SQL/img/screen-shot-2017-08-02-at-11.14.25-am.png 79.36 KB
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Part 04-Module 01-Lesson 04_Probability/img/48750031.gif 78.6 KB
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Part 07-Module 01-Lesson 03_Explore One Variable/img/807038697.gif 78.25 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/img/862108772.gif 78.25 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/img/861308906.gif 78.25 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/img/48678737.gif 77.74 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/refresh-data-reset-workspace.png 77.73 KB
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Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/img/screen-shot-2017-06-26-at-3.47.37-pm.png 77.21 KB
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Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/img/888998550.gif 71.05 KB
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Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/img/753408539.gif 70.78 KB
Part 04-Module 01-Lesson 07_Bayes Rule/img/48609553.gif 70.7 KB
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Part 03-Module 03-Lesson 02_SQL Joins/img/screen-shot-2017-08-10-at-8.10.13-pm.png 68.17 KB
Part 16-Module 01-Lesson 07_Regressions/img/3063118541.gif 67.51 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/animals-clean.png 67.3 KB
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Part 14-Module 03-Lesson 01_Craft Your Cover Letter/img/cover-letter-intro-good.png 65.95 KB
Part 11-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-git-status-new-project.gif 65.36 KB
Part 03-Module 01-Lesson 01_Anaconda/img/conda-env-export.png 64.05 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/img/48739104.gif 63.85 KB
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Part 03-Module 03-Lesson 02_SQL Joins/img/screen-shot-2017-08-11-at-3.21.34-pm.png 58.51 KB
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Part 03-Module 02-Lesson 04_Programming Workflow for Data Analysis/img/ipython-a3.png 56.08 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/img/48741058.gif 56.01 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/img/python-in-terminal.png 55.88 KB
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Part 04-Module 01-Lesson 06_Conditional Probability/img/48720246.gif 55.25 KB
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Part 04-Module 01-Lesson 03_Admissions Case Study/img/48729170.gif 54.43 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/screenshot-2017-09-26-00.58.09.png 54.36 KB
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Part 03-Module 03-Lesson 01_Basic SQL/img/screen-shot-2017-08-04-at-6.41.07-pm.png 52.61 KB
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Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/img/ma-in-sheets.png 50.94 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/header-bar.png 50.59 KB
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Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/img/screen-shot-2018-06-13-at-6.32.38-pm.png 48.53 KB
Part 13-Module 01-Lesson 03_Udacity Professional Profile/img/screen-shot-2017-12-14-at-3.11.32-pm.png 47.91 KB
Part 09-Module 01-Lesson 02_Design/img/screen-shot-2017-09-03-at-2.28.22-pm.png 47.67 KB
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Part 06-Module 02-Lesson 02_Test a Perceptual Phenomenon/img/stroop-test-2.jpg 43.05 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/img/cover-letter-intro-bad.png 42.28 KB
assets/css/jquery.mCustomScrollbar.min.css 41.83 KB
Part 11-Module 01-Lesson 01_What is Version Control/img/ud123-l1-terminal-config-mac.png 41.49 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/screenshot-2017-09-24-12.53.56.png 41.07 KB
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Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/anaconda.png 37.89 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/img/udacitylogo-copy.png 37.69 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/img/udacitylogo-copy.png 37.69 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/img/market-and-colors.png 37.68 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/img/jupyter.png 36.85 KB
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Part 02-Module 01-Lesson 04_Files and Modules/img/intropy-l4-reading-from-a-file.png 34.94 KB
Part 13-Module 01-Lesson 03_Udacity Professional Profile/img/screen-shot-2017-09-04-at-2.07.44-pm.png 34.07 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/img/intropy-looking-for-python3-big.png 33.89 KB
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Part 02-Module 01-Lesson 03_Data Structures and Loops/img/screen-shot-2017-01-09-at-1.08.23-pm.png 30.91 KB
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Part 06-Module 01-Lesson 01_Welcome to Term 2!/img/screen-shot-2018-07-27-at-1.24.38-pm.png 30.85 KB
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Part 16-Module 01-Lesson 11_Text Learning/img/3006298726.gif 30.28 KB
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Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/05. Assessing Data.html 23.89 KB
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assets/css/fonts/KaTeX_SansSerif-Italic.woff 17.7 KB
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Part 04-Module 01-Lesson 03_Admissions Case Study/13. Case Study in Python.html 17.64 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/25. Notebook + Quiz Interpreting Model Coefficients.html 17.49 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/28. Notebook + Quiz Other Things to Consider.html 17.47 KB
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Part 02-Module 01-Lesson 01_Numbers and Strings/05. Variables I.html 17.3 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/11. Solution Subquery Mania.html 17.27 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/07. Quiz Interpreting Coefficients in MLR.html 17.16 KB
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Part 18-Module 01-Lesson 05_Scripting/22. Quiz The Standard Library.html 16.59 KB
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Part 04-Module 01-Lesson 07_Bayes Rule/36. Learning Objectives - Bayes' Rule.html 16.5 KB
Part 18-Module 01-Lesson 03_Control Flow/02. Conditional Statements.html 16.48 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/30. Quiz Show Me.html 16.42 KB
assets/css/fonts/KaTeX_SansSerif-Regular.woff 16.39 KB
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Part 04-Module 01-Lesson 11_Confidence Intervals/04. Notebook + Quiz Building Confidence Intervals.html 16.24 KB
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Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/09. Code with Branches III.html 16.2 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/06. Notebook + Quiz Difference in Means.html 16.01 KB
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Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/08. Code with Branches II.html 15.86 KB
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Part 18-Module 01-Lesson 02_Data Types and Operators/14. Quiz Strings.html 15.63 KB
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Part 02-Module 01-Lesson 01_Numbers and Strings/10. Types and Type Conversion.html 15.48 KB
Part 08-Module 02-Lesson 01_Gathering Data/18. Mashup APIs, Downloading Files Programmatically, JSON.html 15.43 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/11. Quiz Combining Data.html 15.32 KB
Part 04-Module 01-Lesson 16_Logistic Regression/08. Notebook + Quiz Interpret Results.html 15.31 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/img/lead-3.png 15.29 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/26. Text Marks Filters II.html 15.28 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/10. Quizzes On Scatter Plots.html 15.25 KB
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Part 08-Module 02-Lesson 01_Gathering Data/06. Flat File Structure.html 15.23 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/19. Quiz Aggregations.html 15.17 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Boolean Expressions for Conditions.html 15.16 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/36. Quiz Compound Data Structures.html 15.14 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/18. Measures of Center (Mode).html 15.13 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Relational Database Structure.html 15.08 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/27. Quiz + Text Recap Next Steps.html 15.08 KB
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Part 09-Module 01-Lesson 02_Design/20. Quizzes on Data Story Telling.html 14.99 KB
Part 07-Module 02-Lesson 01_Explore and Summarize Data/Project Rubric - Explore and Summarize Data.html 14.93 KB
Part 02-Module 01-Lesson 04_Files and Modules/10. Using Online Resources.html 14.91 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/01. Introduction-TdopVWltgqM.en.vtt 14.89 KB
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Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/45. Quiz Table Calculations.html 14.81 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/img/lag.png 14.8 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Quiz Clean (Test).html 14.8 KB
Part 11-Module 01-Lesson 02_Create A Git Repo/02. Create A Repo From Scratch.html 14.78 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/24. Drawing Conclusions Quiz.html 14.77 KB
Part 18-Module 01-Lesson 04_Functions/02. Defining Functions.html 14.76 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/17. Quiz Difficulties in AB Testing.html 14.75 KB
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Part 04-Module 01-Lesson 12_Hypothesis Testing/11. Quiz Types of Errors - Part III.html 14.64 KB
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Part 02-Module 01-Lesson 01_Numbers and Strings/11. String Methods I.html 14.59 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. Variables and Assignment Operators.html 14.58 KB
Part 04-Module 01-Lesson 16_Logistic Regression/05. Notebook + Quiz Fitting Logistic Regression in Python.html 14.55 KB
Part 04-Module 01-Lesson 14_Regression/11. Quiz What Defines A Line - Notation Quiz.html 14.52 KB
Part 08-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces).html 14.52 KB
Part 18-Module 01-Lesson 05_Scripting/04. [For Windows] Configuring Git Bash to Run Python.html 14.49 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/img/screen-shot-2018-08-15-at-9.46.40-am.png 14.47 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/img/screen-shot-2018-08-15-at-9.46.40-am.png 14.47 KB
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Part 02-Module 01-Lesson 01_Numbers and Strings/08. Strings I.html 14.42 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/24. Text Marks Filters I.html 14.38 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/23. Quiz Lists and Membership Operators.html 14.38 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/46. Text Recap.html 14.37 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/21. Text Hierarchies.html 14.35 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/16. [Optional] Text Linear Model Assumptions.html 14.32 KB
Part 08-Module 03-Lesson 01_Assessing Data/05. Unclean Data Dirty vs. Messy 2.html 14.3 KB
Part 03-Module 03-Lesson 01_Basic SQL/06. Video Why SQL.html 14.26 KB
Part 18-Module 01-Lesson 03_Control Flow/29. Quiz Zip and Enumerate.html 14.26 KB
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1.html 14.25 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess (Intro).html 14.23 KB
Part 18-Module 01-Lesson 03_Control Flow/10. For Loops.html 14.21 KB
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Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Quiz Gather (Unzip File).html 14.17 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/48. Moving Averages.html 14.14 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Video Why SQL.html 14.12 KB
Part 04-Module 01-Lesson 16_Logistic Regression/30. Notebook + Quiz Model Diagnostics.html 14.06 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/06. Quiz Variables and Assignment Operators.html 14.06 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/14. Text Worksheets.html 14.05 KB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet.html 14 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/28. Quiz Notation for the Mean.html 13.97 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/16. Quiz Assess (Programmatic).html 13.97 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/03. Motivation for Data Visualization.html 13.95 KB
Part 18-Module 01-Lesson 05_Scripting/28. Online Resources.html 13.94 KB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz.html 13.94 KB
Part 18-Module 01-Lesson 03_Control Flow/18. Quiz Iterating Through Dictionaries.html 13.91 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Git and Version Control Terminology.html 13.86 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/08. Packages Overview Quiz.html 13.81 KB
Part 03-Module 03-Lesson 01_Basic SQL/12. Text + Quiz Your First Query.html 13.79 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/04. Text Outline of Topics Covered.html 13.78 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/15. Homework 1 Final Quiz on Measures Spread.html 13.78 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/18. Quiz What is a p-value Anyway.html 13.75 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/34. Quiz More With Dictionaries.html 13.72 KB
Part 08-Module 03-Lesson 01_Assessing Data/15. Quality Programatic Assessment 1-l-FhDkQRclA.en.vtt 13.71 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/19. Notebook + Quiz Multicollinearity VIFs.html 13.71 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML File Structure.html 13.7 KB
assets/css/fonts/KaTeX_SansSerif-Regular.woff2 13.7 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/28. Quiz Tuples.html 13.69 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/39. Quiz Sets.html 13.66 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/10. Text + Quiz Your First Query.html 13.65 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/03. Defining Functions II.html 13.64 KB
Part 18-Module 01-Lesson 03_Control Flow/16. Building Dictionaries.html 13.57 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/02. Efficiency of Binary Search-7WbRB7dSyvc.en-US.vtt 13.54 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/02. Efficiency of Binary Search-7WbRB7dSyvc.en.vtt 13.54 KB
assets/css/fonts/KaTeX_Script-Regular.woff 13.53 KB
Part 03-Module 03-Lesson 02_SQL Joins/08. Quiz Primary - Foreign Key Relationship.html 13.51 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/03. Designing the Program.html 13.49 KB
Part 03-Module 03-Lesson 02_SQL Joins/17. Solutions LEFT and RIGHT JOIN .html 13.48 KB
Part 03-Module 03-Lesson 01_Basic SQL/14. Text Formatting Best Practices.html 13.42 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/11. Subquery Solution Video-Y6S3S0LsMrw.pt-BR.vtt 13.37 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/03. Data in NumPy.html 13.36 KB
Part 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn.html 13.3 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/04. Viewing Modified Files.html 13.29 KB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy.html 13.27 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/12. Text Formatting Best Practices.html 13.27 KB
Part 03-Module 03-Lesson 02_SQL Joins/20. Solutions Last Check.html 13.25 KB
Part 15-Module 02-Lesson 06_Graphs/08. Graph Representation Practice.html 13.24 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/Project Rubric - Resume Review Project (Career Change).html 13.23 KB
Part 16-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression.html 13.21 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/Project Rubric - Resume Review Project (Entry-level).html 13.19 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/06. Having Git Ignore Files.html 13.17 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Changing How Git Log Displays Information.html 13.14 KB
Part 08-Module 05-Lesson 01_Wrangle and Analyze Data/Project Rubric - Wrangle and Analyze Data.html 13.14 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/19. String Methods.html 13.11 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/14. [Optional] Notebook + Quiz Other Encodings.html 13.09 KB
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Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/02. Defining Functions I.html 13.02 KB
Part 18-Module 01-Lesson 03_Control Flow/15. Quiz Match Inputs To Outputs.html 12.99 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/Project Rubric - Resume Review Project (Prior Industry Experience).html 12.97 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/25. List Methods.html 12.97 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/media/unnamed-59153-0.gif 12.94 KB
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Part 18-Module 01-Lesson 03_Control Flow/23. Quiz While Loops.html 12.93 KB
Part 18-Module 01-Lesson 05_Scripting/26. Third-Party Libraries.html 12.91 KB
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness.html 12.9 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set.html 12.9 KB
Part 03-Module 03-Lesson 02_SQL Joins/11. Quiz JOIN Questions Part I.html 12.87 KB
assets/css/fonts/KaTeX_Size1-Regular.ttf 12.86 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/22. Quiz Clean (Code 2).html 12.84 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading and Writing Files.html 12.83 KB
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Part 09-Module 01-Lesson 02_Design/11. Bad Visual Quizzes (Part II).html 12.79 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/18. Text Aggregations.html 12.78 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/07. Template and Software.html 12.73 KB
Part 09-Module 02-Lesson 01_Create a Tableau Story/02. Project Details.html 12.73 KB
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Part 08-Module 03-Lesson 01_Assessing Data/16. Quality Programmatic Assessment 2.html 12.72 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/32. Text Small Multiples Dual Axis.html 12.71 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/10. Dummy Variables.html 12.69 KB
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality.html 12.68 KB
Part 08-Module 02-Lesson 01_Gathering Data/14. Text Files in Python.html 12.67 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/05. Quiz Setting Up Hypothesis Tests.html 12.67 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Quiz Gather (Download).html 12.66 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/20. String Methods.html 12.66 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/21. Notebook + Quiz Central Limit Theorem - Part III.html 12.65 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/11. Subquery Solution Video-Y6S3S0LsMrw.en.vtt 12.65 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/44. Text Table Calculations.html 12.63 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means.html 12.62 KB
Part 03-Module 03-Lesson 01_Basic SQL/08. Text + Quiz Types of Databases.html 12.62 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/08. Integers and Floats.html 12.6 KB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree.html 12.59 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/07. Quiz More On Subqueries.html 12.58 KB
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2.html 12.56 KB
Part 08-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2.html 12.56 KB
Part 08-Module 03-Lesson 01_Assessing Data/15. Quality Programatic Assessment 1-l-FhDkQRclA.pt-BR.vtt 12.55 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/26. Text Descriptive Statistics Summary .html 12.54 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/12. Quizzes UNION.html 12.53 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/03. Quiz Arithmetic Operators.html 12.51 KB
Part 13-Module 01-Lesson 02_LinkedIn Review/Project Rubric - LinkedIn Profile Review Project.html 12.5 KB
Part 02-Module 01-Lesson 04_Files and Modules/09. Third-Party Libraries.html 12.5 KB
Part 03-Module 03-Lesson 01_Basic SQL/49. Text Recap Looking Ahead.html 12.47 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/05. Tableau Dashboards Stories with Trina-i9xslfFp80g.pt-BR.vtt 12.46 KB
Part 16-Module 01-Lesson 07_Regressions/39. Bonus Target and Features.html 12.46 KB
Part 15-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-qRv1wrtgsmM.zh-CN.vtt 12.45 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces.html 12.41 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/13. Advanced Standard Deviation and Variance.html 12.41 KB
Part 03-Module 03-Lesson 01_Basic SQL/16. Quiz LIMIT.html 12.4 KB
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Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/02. Text Installing Tableau.html 12.36 KB
Part 03-Module 03-Lesson 02_SQL Joins/19. Quiz Last Check.html 12.36 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/10. Text Combining Data Recap.html 12.35 KB
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3.html 12.35 KB
Part 03-Module 03-Lesson 01_Basic SQL/04. Quiz ERD Fundamentals.html 12.34 KB
Part 04-Module 01-Lesson 14_Regression/09. Correlation Coefficient Quizzes.html 12.33 KB
Part 08-Module 03-Lesson 01_Assessing Data/13. Data Quality Dimensions 2.html 12.32 KB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process.html 12.32 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/18. Notebook + Quiz Central Limit Theorem.html 12.26 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/14. Quiz LIMIT.html 12.26 KB
Part 09-Module 01-Lesson 02_Design/10. Bad Visual Quizzes (Part I).html 12.25 KB
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split.html 12.25 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means.html 12.24 KB
Part 08-Module 03-Lesson 01_Assessing Data/15. Quality Programatic Assessment 1-l-FhDkQRclA.zh-CN.vtt 12.24 KB
Part 03-Module 03-Lesson 01_Basic SQL/03. Video + Text The Parch Posey Database.html 12.24 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/19. Quiz Shape and Outliers (What's the Impact).html 12.24 KB
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split.html 12.24 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/19. Notebook + Quiz Central Limit Theorem - Part II.html 12.23 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/32. Solutions CASE.html 12.23 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/38. Quiz Groups.html 12.23 KB
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split.html 12.22 KB
Part 04-Module 01-Lesson 14_Regression/20. Notebook + Quiz Your Turn - Part II.html 12.21 KB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2.html 12.2 KB
Part 08-Module 02-Lesson 01_Gathering Data/17. JSON Files in Python.html 12.2 KB
Part 15-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-qRv1wrtgsmM.pt-BR.vtt 12.19 KB
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Part 03-Module 01-Lesson 02_Jupyter Notebooks/01. What are Jupyter notebooks.html 12.19 KB
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Part 08-Module 02-Lesson 01_Gathering Data/10. HTML Files in Python.html 12.17 KB
Part 03-Module 03-Lesson 01_Basic SQL/05. Text Map of SQL Content.html 12.17 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/08. Inspecting Data Types.html 12.16 KB
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Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/24. Notebook + Quiz Bootstrapping.html 12.13 KB
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Part 15-Module 02-Lesson 02_List-Based Collections/07. Linked List Practice.html 12.06 KB
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Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters.html 12.02 KB
Part 04-Module 01-Lesson 08_Python Probability Practice/06. Cancer Test Results.html 12.01 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months.html 12.01 KB
assets/css/fonts/KaTeX_Script-Regular.woff2 11.99 KB
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Part 16-Module 01-Lesson 04_Decision Trees/09. Decision Tree Accuracy.html 11.85 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld.html 11.81 KB
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Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Video Notation for Parameters vs. Statistics.html 11.78 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own.html 11.75 KB
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Part 08-Module 05-Lesson 01_Wrangle and Analyze Data/04. Twitter API.html 11.71 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/31. Dictionaries and Identity Operators.html 11.71 KB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents.html 11.7 KB
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Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/07. Iterative Programming I.html 11.61 KB
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Part 04-Module 01-Lesson 15_Multiple Linear Regression/24. Text Interpreting Interactions.html 11.56 KB
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Part 03-Module 03-Lesson 03_SQL Aggregations/23. HAVING.html 11.53 KB
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Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA.html 11.51 KB
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Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays.html 11.49 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions.html 11.47 KB
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Part 18-Module 01-Lesson 03_Control Flow/32. Quiz List Comprehensions.html 11.43 KB
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Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Implementing the Program II.html 11.38 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/19. Quiz Calculating a p-value.html 11.38 KB
Part 16-Module 01-Lesson 07_Regressions/41. Extracting Slope and Intercept.html 11.37 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara.html 11.37 KB
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Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1.html 11.37 KB
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Part 13-Module 01-Lesson 02_LinkedIn Review/img/career-portal-sidebar.png 11.37 KB
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Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/img/career-portal-sidebar.png 11.37 KB
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Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/img/career-portal-sidebar.png 11.37 KB
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Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/20. Quiz ORDER BY Part II.html 11.34 KB
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Part 08-Module 02-Lesson 01_Gathering Data/08. Source Web Scraping.html 11.3 KB
Part 18-Module 01-Lesson 03_Control Flow/17. Iterating Through Dictionaries with For Loops.html 11.3 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/21. Exploring Data with Visuals Quiz.html 11.29 KB
Part 04-Module 01-Lesson 14_Regression/18. Notebook + Quiz How to Interpret the Results.html 11.27 KB
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Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line.html 11.25 KB
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7.html 11.23 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test.html 11.23 KB
Part 18-Module 01-Lesson 03_Control Flow/09. Solution Boolean Expressions for Conditions.html 11.22 KB
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Part 03-Module 03-Lesson 01_Basic SQL/07. Video How Databases Store Data.html 11.13 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/10. Finishing Touches.html 11.13 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/10. Sets.html 11.13 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability.html 11.11 KB
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Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices.html 11.09 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/09. Matrix Transposes-NVK5xCY3CZE.pt-BR.vtt 11.08 KB
Part 07-Module 02-Lesson 01_Explore and Summarize Data/02. Project Details.html 11.08 KB
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities.html 11.07 KB
Part 08-Module 02-Lesson 01_Gathering Data/23. Relational Databases in Python.html 11.07 KB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition.html 11.06 KB
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix.html 11.06 KB
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Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/06. Python Programming Setup.html 11.05 KB
Part 11-Module 01-Lesson 01_What is Version Control/04. MacLinux Setup.html 11.03 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/07. Solution Variables and Assignment Operators.html 11.03 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/13. Conclusions Using Groupby.html 11.03 KB
Part 02-Module 01-Lesson 04_Files and Modules/01. Tuples.html 11.03 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity.html 11.03 KB
Part 03-Module 03-Lesson 01_Basic SQL/34. Video LIKE.html 11.03 KB
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data.html 11.02 KB
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Part 03-Module 03-Lesson 01_Basic SQL/41. Quiz NOT.html 11.01 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited.html 11.01 KB
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall.html 11 KB
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Part 04-Module 01-Lesson 08_Python Probability Practice/07. Conditional Probability Bayes Rule Quiz.html 11 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/29. Text Show Me.html 11 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/06. Video How Databases Store Data.html 10.99 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/17. Text Recap + Next Steps.html 10.98 KB
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Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/17. Quiz Assess (Tidiness).html 10.98 KB
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Part 18-Module 01-Lesson 05_Scripting/02. Python Installation.html 10.97 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders.html 10.94 KB
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Part 04-Module 01-Lesson 16_Logistic Regression/29. Screencast Model Diagnostics in Python - Part I.html 10.9 KB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components.html 10.9 KB
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Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Iterative Programming II.html 10.83 KB
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Part 04-Module 01-Lesson 16_Logistic Regression/03. Quiz Logistic Regression Quick Check.html 10.81 KB
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Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems.html 10.81 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/43. Timing Your NB Classifier.html 10.75 KB
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers.html 10.74 KB
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Part 08-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment.html 10.71 KB
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Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers.html 10.69 KB
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Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice.html 10.68 KB
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Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/03. Asking Questions.html 10.67 KB
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Part 18-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate.html 10.67 KB
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Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall.html 10.66 KB
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Part 04-Module 01-Lesson 12_Hypothesis Testing/07. Quiz Types of Errors - Part I.html 10.65 KB
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Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature.html 10.63 KB
Part 03-Module 03-Lesson 01_Basic SQL/38. Quiz IN.html 10.62 KB
Part 15-Module 02-Lesson 02_List-Based Collections/10. Stack Practice.html 10.62 KB
Part 03-Module 03-Lesson 01_Basic SQL/20. Solutions ORDER BY.html 10.62 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Video Important Final Points.html 10.62 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/01. Your first project.html 10.61 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/05. Commas vs Periods.html 10.61 KB
Part 16-Module 01-Lesson 03_SVM/02. Separating Line.html 10.61 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/03. Launching the notebook server.html 10.61 KB
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two.html 10.61 KB
Part 16-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression.html 10.6 KB
Part 18-Module 01-Lesson 05_Scripting/25. Quiz Techniques for Importing Modules.html 10.6 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/10. Getting Help.html 10.6 KB
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Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features.html 10.59 KB
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Part 16-Module 01-Lesson 13_PCA/34. Explained Variance of Each PC.html 10.59 KB
Part 16-Module 01-Lesson 11_Text Learning/07. Low-Information Words.html 10.59 KB
Part 18-Module 01-Lesson 03_Control Flow/11. Practice For Loops.html 10.59 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/13. Other Language Associated with Confidence Intervals.html 10.58 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/24. Other Things to Consider - What if Our Sample is Large.html 10.58 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases.html 10.58 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/21. Solutions ORDER BY Part II.html 10.58 KB
Part 03-Module 04-Lesson 01_Investigate a Dataset/Project Rubric - Investigate a Dataset.html 10.58 KB
Part 16-Module 01-Lesson 13_PCA/11. Practice Finding New Axes.html 10.58 KB
Part 08-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.ar.vtt 10.57 KB
Part 08-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.ar.vtt 10.57 KB
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Part 16-Module 01-Lesson 04_Decision Trees/38. Speeding Up Via Feature Selection 1.html 10.57 KB
Part 07-Module 01-Lesson 03_Explore One Variable/22. Transforming Data.html 10.56 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/46. Solutions OR.html 10.56 KB
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Part 18-Module 01-Lesson 02_Data Types and Operators/29. Sets.html 10.56 KB
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Part 16-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3.html 10.55 KB
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality.html 10.55 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/34. How Many True Positives.html 10.55 KB
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6.html 10.54 KB
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Part 18-Module 01-Lesson 03_Control Flow/31. List Comprehensions.html 10.54 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/24. Solutions WHERE.html 10.53 KB
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5.html 10.53 KB
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability.html 10.53 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective.html 10.52 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/05. Quiz 5 Number Summary Practice.html 10.52 KB
Part 03-Module 03-Lesson 01_Basic SQL/24. Video WHERE.html 10.52 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/09. Getting Help.html 10.52 KB
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance.html 10.51 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/13. How Do We Choose Between Hypotheses.html 10.51 KB
Part 16-Module 01-Lesson 07_Regressions/42. Regression Score Training Data.html 10.51 KB
Part 03-Module 03-Lesson 01_Basic SQL/36. Solutions LIKE.html 10.5 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together.html 10.5 KB
Part 03-Module 03-Lesson 01_Basic SQL/35. Quiz LIKE.html 10.5 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color.html 10.5 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. Video + Quiz Performance Tuning 1.html 10.5 KB
Part 03-Module 03-Lesson 01_Basic SQL/15. Video LIMIT.html 10.5 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/11. Exploring with Visuals.html 10.49 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review.html 10.48 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview.html 10.48 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/36. Quiz IN.html 10.48 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/05. Data Analysis Process Overview.html 10.48 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/18. Solutions ORDER BY.html 10.48 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut.html 10.48 KB
Part 03-Module 03-Lesson 01_Basic SQL/33. Text Introduction to Logical Operators.html 10.47 KB
Part 16-Module 01-Lesson 07_Regressions/45. Salary vs. LTI for Predicting Bonus.html 10.47 KB
Part 18-Module 01-Lesson 03_Control Flow/20. While Loops.html 10.47 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/12. Common Types of Hypothesis Tests.html 10.47 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/11. NumPy Quiz.html 10.47 KB
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test.html 10.47 KB
Part 03-Module 03-Lesson 01_Basic SQL/39. Solutions IN.html 10.46 KB
Part 07-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons.html 10.46 KB
Part 03-Module 01-Lesson 01_Anaconda/02. What is Anaconda.html 10.46 KB
Part 16-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy.html 10.46 KB
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Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/16. Video ORDER BY.html 10.45 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function.html 10.45 KB
Part 04-Module 01-Lesson 08_Python Probability Practice/03. Probability Quiz.html 10.45 KB
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Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1.html 10.44 KB
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Part 03-Module 03-Lesson 01_Basic SQL/09. Video Types of Statements.html 10.44 KB
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Part 16-Module 01-Lesson 13_PCA/35. How Many PCs to Use.html 10.42 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/33. Recall of Your POI Identifier.html 10.42 KB
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Part 18-Module 01-Lesson 02_Data Types and Operators/24. Solution List and Membership Operators.html 10.42 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data.html 10.41 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/31. Number of True Positives.html 10.39 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Video Shape.html 10.38 KB
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data.html 10.38 KB
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Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout.html 10.37 KB
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2.html 10.37 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/03. Integers and Floats.html 10.37 KB
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters.html 10.37 KB
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Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/34. Solutions LIKE.html 10.36 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/04. Program Structure and Schedule.html 10.36 KB
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Part 16-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer.html 10.35 KB
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Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/31. Text Introduction to Logical Operators.html 10.33 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/32. Unpacking Into Precision and Recall.html 10.32 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/16. Type and Type Conversion.html 10.32 KB
Part 16-Module 01-Lesson 04_Decision Trees/40. SelectPercentile and Complexity.html 10.32 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/25. Video WHERE with Non-Numeric Data.html 10.31 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean.html 10.31 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means.html 10.31 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/16. Precision and Recall.html 10.31 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/12. Video What Can You Create In Tableau.html 10.3 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/07. Video Types of Statements.html 10.29 KB
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again).html 10.29 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/10. Questions for a Dataset.html 10.28 KB
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Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/07. Price by Cut.html 10.27 KB
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Part 16-Module 01-Lesson 03_SVM/36. Extracting Predictions from an SVM.html 10.27 KB
Part 18-Module 01-Lesson 03_Control Flow/14. Solution For Loops Quiz.html 10.27 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure.html 10.27 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/18. Video Multicollinearity VIFs.html 10.25 KB
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2.html 10.25 KB
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Part 16-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors.html 10.25 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated.html 10.24 KB
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Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/16. Exploring Your Friends' Birthdays.html 10.24 KB
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1.html 10.23 KB
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions.html 10.23 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/08. Univariate Plots.html 10.23 KB
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Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces.html 10.22 KB
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Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem.html 10.21 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds.html 10.2 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/11. Solutions Your First Query Solution.html 10.2 KB
Part 16-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn.html 10.2 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/15. Solutions LIMIT.html 10.2 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/39. Getting Started with Mini-Projects.html 10.18 KB
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count.html 10.17 KB
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Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz.html 10.15 KB
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Part 03-Module 03-Lesson 01_Basic SQL/21. Video ORDER BY Part II.html 10.15 KB
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier.html 10.14 KB
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Part 03-Module 03-Lesson 01_Basic SQL/40. Video NOT.html 10.13 KB
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Part 13-Module 01-Lesson 03_Udacity Professional Profile/Project Rubric - Udacity Professional Profile Review.html 10.03 KB
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Part 18-Module 01-Lesson 05_Scripting/09. Quiz Scripting with Raw Input.html 10 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/19. Video ORDER BY Part II.html 10 KB
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK.html 10 KB
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Part 04-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders.html 9.98 KB
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Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer.html 9.97 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/36. False Positives.html 9.96 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/28. Number of POIs in Test Set.html 9.96 KB
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Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/16. Measures of Center (Median).html 9.95 KB
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Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/12. Breaking Programs Into Smaller Pieces.html 9.93 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson.html 9.93 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification.html 9.92 KB
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Part 16-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma.html 9.91 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. Video UNION.html 9.91 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/Project Rubric - Craft Your Cover Letter.html 9.91 KB
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Part 16-Module 01-Lesson 13_PCA/36. F1 Score vs. No. of PCs Used.html 9.88 KB
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Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/21. Quiz Percentiles.html 9.88 KB
Part 18-Module 01-Lesson 05_Scripting/03. Install Python Using Anaconda.html 9.87 KB
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Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing.html 9.85 KB
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Part 03-Module 03-Lesson 01_Basic SQL/02. Video The Parch Posey Database.html 9.84 KB
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Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/02. Course Outline.html 9.83 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/21. Solutions DISTINCT.html 9.83 KB
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Part 16-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees.html 9.82 KB
Part 16-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn.html 9.82 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/08. Magic keywords.html 9.82 KB
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Part 18-Module 01-Lesson 05_Scripting/06. Programming Environment Setup.html 9.81 KB
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Part 04-Module 01-Lesson 15_Multiple Linear Regression/01. Video Introduction.html 9.78 KB
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day.html 9.76 KB
Part 03-Module 03-Lesson 01_Basic SQL/01. Video SQL Introduction.html 9.76 KB
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Part 04-Module 01-Lesson 13_Case Study AB tests/10. Metric - Enrollment Rate.html 9.72 KB
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Part 02-Module 01-Lesson 01_Numbers and Strings/07. Comparison Operators.html 9.71 KB
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Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/47. Video What's Next.html 9.7 KB
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Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/03. Video The Parch Posey Database.html 9.7 KB
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Part 03-Module 02-Lesson 01_The Data Analysis Process/04. Setting Up Your Programming Environment.html 9.69 KB
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Part 03-Module 03-Lesson 02_SQL Joins/06. Text ERD Reminder.html 9.66 KB
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Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/02. Video SQL Introduction.html 9.61 KB
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Part 09-Module 01-Lesson 01_Introduction to Data Visualization/19. Quiz On Visual Encodings.html 9.52 KB
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Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/08. Scales and Multiple Histograms.html 9.48 KB
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Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/28. Data Wrangling Summary.html 9.47 KB
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Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Video Window Functions 1.html 9.33 KB
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Part 18-Module 01-Lesson 02_Data Types and Operators/33. Solution Dictionaries and Identity Operators.html 9.32 KB
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Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Video Standard Deviation Calculation.html 9.31 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/21. Conclusions in Hypothesis Testing.html 9.31 KB
Part 04-Module 01-Lesson 14_Regression/08. Correlation Coefficients.html 9.3 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/04. Solution Arithmetic Operators.html 9.3 KB
Part 08-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Phase II Clinical Trial Data.html 9.3 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/12. Solution Booleans, Comparison and Logical Operators.html 9.29 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/15. Correct Interpretations of Confidence Intervals.html 9.29 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/15. Quiz Analyzing Multiple Metrics.html 9.29 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/05. Screencast + Text How Does MLR Work.html 9.29 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/17. Quiz Comparing a Row to Previous Row.html 9.29 KB
Part 13-Module 01-Lesson 02_LinkedIn Review/01. Using LinkedIn.html 9.29 KB
Part 04-Module 01-Lesson 16_Logistic Regression/09. Video Model Diagnostics + Performance Metrics.html 9.29 KB
Part 16-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses.html 9.29 KB
Part 18-Module 01-Lesson 03_Control Flow/19. Solution Iterating Through Dictionaries.html 9.28 KB
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text.html 9.28 KB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R.html 9.28 KB
Part 03-Module 04-Lesson 01_Investigate a Dataset/02. Project Details.html 9.28 KB
Part 08-Module 02-Lesson 01_Gathering Data/04. Navigating Your Working Directory and File IO.html 9.28 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/29. Missing POIs 1 (optional).html 9.27 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/25. Follow the Money.html 9.27 KB
Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation.html 9.27 KB
Part 04-Module 02-Lesson 01_Analyze AB Test Results/02. Quiz 1 Understanding the Dataset.html 9.27 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/09. Text Dummy Variables.html 9.27 KB
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable.html 9.26 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/04. Examples.html 9.26 KB
Part 15-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-i3RTW83wI1Q.zh-CN.vtt 9.26 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/37. Solution Compound Data Structions.html 9.25 KB
Part 02-Module 02-Lesson 01_Python Project/Project Rubric - Explore US Bikeshare Data.html 9.25 KB
Part 02-Module 02-Lesson 01_Python Project/03. Notebook interface.html 9.25 KB
Part 16-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components.html 9.25 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/03. Accuracy vs. Training Set Size-9w1Yi5nMNgw.ar.vtt 9.25 KB
Part 08-Module 04-Lesson 01_Cleaning Data/07. Quiz and Solution Notebooks.html 9.24 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format.html 9.23 KB
Part 16-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation.html 9.21 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Video The Background of Bootstrapping.html 9.21 KB
Part 15-Module 01-Lesson 05_Interview Practice/Project Rubric - Interview Practice (Data Analyst).html 9.2 KB
Part 07-Module 01-Lesson 02_R Basics/10. Read and Subset Data-UdniaeLsViQ.ar.vtt 9.2 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/08. Video Dummy Variables.html 9.2 KB
Part 16-Module 01-Lesson 12_Feature Selection/28. Use TfIdf to Get the Most Important Word.html 9.2 KB
Part 04-Module 01-Lesson 14_Regression/03. Quiz Machine Learning Big Picture.html 9.19 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Video Measures of Center (Mode).html 9.19 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety.html 9.19 KB
Part 16-Module 01-Lesson 13_PCA/06. PCA for Data Transformation.html 9.19 KB
Part 16-Module 01-Lesson 03_SVM/38. Final Thoughts on Deploying SVMs.html 9.19 KB
Part 09-Module 02-Lesson 01_Create a Tableau Story/Project Rubric - Create a Tableau Story.html 9.18 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/01. Introduction.html 9.18 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/10. Transposes in NumPy.html 9.18 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/14. Quiz WITH.html 9.18 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/05. Element-wise Operations in NumPy.html 9.17 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution.html 9.17 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/02. Video Multiple Linear Regression.html 9.16 KB
Part 16-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA.html 9.16 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Video Introduction to Sampling Distributions Part III.html 9.16 KB
Part 16-Module 01-Lesson 03_SVM/28. SVM Author ID Accuracy.html 9.16 KB
Part 16-Module 01-Lesson 03_SVM/35. Optimized RBF vs. Linear SVM Accuracy.html 9.16 KB
Part 16-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling.html 9.15 KB
Part 16-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro.html 9.15 KB
Part 16-Module 01-Lesson 13_PCA/26. Applying PCA to Real Data.html 9.15 KB
Part 08-Module 04-Lesson 01_Cleaning Data/17. Flashforward-rfMu3f9O9hQ.zh-CN.vtt 9.15 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/24. Video Better Way.html 9.14 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price.html 9.14 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/11. Fixing Data Types Pt 3.html 9.14 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins.html 9.14 KB
Part 15-Module 02-Lesson 05_Trees/14. BST Practice.html 9.14 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts.html 9.13 KB
Part 18-Module 01-Lesson 03_Control Flow/22. Solution While Loops Practice.html 9.12 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/03. Video NULLs and Aggregation.html 9.12 KB
Part 18-Module 01-Lesson 04_Functions/14. [Optional] Iterators and Generators.html 9.12 KB
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands).html 9.12 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/38. Conclusion.html 9.12 KB
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2.html 9.11 KB
Part 04-Module 01-Lesson 14_Regression/14. Text The Regression Closed Form Solution.html 9.11 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting.html 9.11 KB
Part 03-Module 03-Lesson 02_SQL Joins/14. Video LEFT and RIGHT JOINs.html 9.1 KB
Part 16-Module 01-Lesson 13_PCA/31. Eigenfaces Code.html 9.1 KB
Part 16-Module 01-Lesson 13_PCA/29. When to Use PCA.html 9.1 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Video Bootstrapping.html 9.09 KB
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram.html 9.09 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/06. Video Multiple Linear Regression Model Results.html 9.09 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/05. Recursion Practice.html 9.08 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/06. Video What if We Only Want One Number.html 9.08 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/15. Merging Datasets.html 9.08 KB
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing.html 9.07 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/03. Video Weekdays vs. Weekends What is the Difference.html 9.07 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/06. Python The Basics.html 9.06 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Video Why the Standard Deviation.html 9.06 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/32. Missing POIs 4 (optional).html 9.05 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/25. Video DATE Functions.html 9.05 KB
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization.html 9.04 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Video Summary.html 9.04 KB
Part 03-Module 02-Lesson 04_Programming Workflow for Data Analysis/02. Analyzing with IPython.html 9.04 KB
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1.html 9.04 KB
Part 07-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size.html 9.04 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/18. Solution Type and Type Conversion.html 9.04 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Video Data Types (Continuous vs. Discrete).html 9.03 KB
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers.html 9.03 KB
Part 08-Module 03-Lesson 01_Assessing Data/14. Programmatic Assessment.html 9.03 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization.html 9.03 KB
Part 16-Module 01-Lesson 12_Feature Selection/23. Overfitting a Decision Tree 1.html 9.03 KB
Part 04-Module 02-Lesson 01_Analyze AB Test Results/05. Quiz 4 Probability.html 9.02 KB
Part 16-Module 01-Lesson 03_SVM/32. Deploy an RBF Kernel.html 9.02 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Video Percentiles.html 9.02 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/05. Write the Body.html 9 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/15. Gapminder Data.html 9 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/05. Text Subquery Formatting.html 9 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price.html 8.99 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/09. Video MIN MAX.html 8.99 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/17. Video Calculating the p-value.html 8.99 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship.html 8.99 KB
Part 18-Module 01-Lesson 03_Control Flow/01. Introduction.html 8.99 KB
Part 08-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Phase II Clinical Trial Data.html 8.99 KB
Part 16-Module 01-Lesson 03_SVM/16. Visualizing the New Feature.html 8.98 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/04. Program Structure and Schedule.html 8.98 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/19. Video DISTINCT.html 8.98 KB
Part 16-Module 01-Lesson 03_SVM/37. How Many Chris Emails Predicted.html 8.98 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/18. Assess (Summary).html 8.98 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data-TgkBAtaTqJk.ar.vtt 8.97 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/13. Mean Price by Clarity.html 8.97 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/16. Solutions COALESCE.html 8.96 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/03. Python Dictionaries.html 8.96 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/13. Size of the Enron Dataset.html 8.96 KB
Part 12-Module 01-Lesson 01_GitHub Review/Project Rubric - Optimize Your GitHub Profile.html 8.95 KB
Part 08-Module 02-Lesson 01_Gathering Data/10. HTML Files in Python 1-0VZumC18UvQ.ar.vtt 8.95 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/18. Query the Dataset 1.html 8.95 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Video Data Types (Ordinal vs. Nominal).html 8.94 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study-ahaxt6UKxQw.zh-CN.vtt 8.94 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate.html 8.94 KB
Part 16-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video.html 8.94 KB
Part 16-Module 01-Lesson 03_SVM/11. SVM Decision Boundary.html 8.93 KB
Part 15-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-i3RTW83wI1Q.pt-BR.vtt 8.93 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/20. Quiz DISTINCT.html 8.92 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/04. Recursion-_aI2Jch6Epk.pt-BR.vtt 8.92 KB
Part 08-Module 03-Lesson 01_Assessing Data/10. Assessing vs. Exploring.html 8.92 KB
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression.html 8.92 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/15. Building Program Pieces II.html 8.91 KB
Part 16-Module 01-Lesson 09_Clustering/12. Sklearn-3zHUAXcoZ7c.ar.vtt 8.9 KB
Part 04-Module 01-Lesson 16_Logistic Regression/31. Video Final Thoughts On Shifting to Machine Learning.html 8.9 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/17. Screencast Multicollinearity VIFs.html 8.9 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/img/intropy-l2-circular-cylinder-rh.svg 8.89 KB
Part 18-Module 01-Lesson 03_Control Flow/12. Solution For Loops Practice.html 8.89 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/10. Video Traditional Confidence Intervals.html 8.89 KB
Part 16-Module 01-Lesson 03_SVM/09. Handoff to Katie.html 8.89 KB
Part 07-Module 02-Lesson 01_Explore and Summarize Data/01. Project Overview.html 8.88 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/10. Video AVG.html 8.88 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/15. Finding POIs in the Enron Data.html 8.88 KB
Part 15-Module 01-Lesson 05_Interview Practice/02. Quiz Analyzing an Interview.html 8.87 KB
Part 16-Module 01-Lesson 03_SVM/13. Nonlinear SVMs.html 8.87 KB
Part 16-Module 01-Lesson 03_SVM/10. SVM in SKlearn.html 8.87 KB
Part 16-Module 01-Lesson 03_SVM/01. Welcome to SVM.html 8.87 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/05. Walkthrough and Dataset.html 8.87 KB
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1.html 8.85 KB
Part 16-Module 01-Lesson 03_SVM/19. Kernel Trick.html 8.85 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/33. Missing POIs 5 (optional).html 8.85 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/30. Video CASE Aggregations.html 8.85 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/27. Dealing with Unfilled Features.html 8.84 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/09. Built-in Functions.html 8.84 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/03. A Definition and An Analogy.html 8.84 KB
Part 04-Module 01-Lesson 16_Logistic Regression/04. Video Fitting Logistic Regression in Python.html 8.84 KB
Part 18-Module 01-Lesson 05_Scripting/19. Solution Reading and Writing Files.html 8.84 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/16. How Many POIs Exist.html 8.83 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/12. Next Steps.html 8.83 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset.html 8.83 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price.html 8.83 KB
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3.html 8.83 KB
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2.html 8.83 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/34. Missing POIs 6 (optional).html 8.83 KB
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2.html 8.82 KB
Part 18-Module 01-Lesson 03_Control Flow/27. Solution Break, Continue.html 8.82 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/12. Datasets and Questions Mini-Project.html 8.82 KB
Part 02-Module 02-Lesson 01_Python Project/Project Description - Explore US Bikeshare Data.html 8.81 KB
Part 04-Module 01-Lesson 16_Logistic Regression/07. Video (ScreenCast) Interpret Results - Part II.html 8.81 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/31. Missing POIs 3 (optional).html 8.81 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Video Why are Sampling Distributions Important.html 8.81 KB
Part 08-Module 03-Lesson 01_Assessing Data/06. Assessment Types vs. Steps.html 8.81 KB
Part 08-Module 02-Lesson 01_Gathering Data/02. Lesson Outline.html 8.81 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1.html 8.81 KB
Part 04-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram.html 8.8 KB
Part 15-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array.html 8.8 KB
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters.html 8.8 KB
Part 16-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter.html 8.8 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.pt-BR.vtt 8.8 KB
Part 04-Module 01-Lesson 04_Probability/17. Even Roll.html 8.8 KB
Part 16-Module 01-Lesson 14_Validation/12. GridSearchCV in sklearn.html 8.8 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/17. Problems with Incomplete Data.html 8.79 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/06. Video SUM.html 8.79 KB
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1.html 8.79 KB
Part 07-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data.html 8.79 KB
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5.html 8.79 KB
Part 04-Module 01-Lesson 16_Logistic Regression/01. Video Introduction.html 8.78 KB
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors.html 8.78 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients.html 8.77 KB
Part 04-Module 01-Lesson 16_Logistic Regression/02. Video Fitting Logistic Regression.html 8.77 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/20. Query the Dataset 3.html 8.77 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Welcome!.html 8.77 KB
Part 04-Module 01-Lesson 04_Probability/13. One Head 1.html 8.76 KB
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means.html 8.76 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/10. String Keys Practice.html 8.76 KB
Part 15-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability.html 8.76 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/09. SQL Subquery Video-10pmKmTI_CA.en.vtt 8.76 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age.html 8.76 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/10. Quiz Subquery Mania.html 8.75 KB
Part 16-Module 01-Lesson 12_Feature Selection/31. Accuracy of the Overfit Tree.html 8.75 KB
Part 16-Module 01-Lesson 12_Feature Selection/09. Univariate Feature Selection.html 8.75 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/15. Solutions Aliases for Multiple Window Functions.html 8.75 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data.html 8.75 KB
Part 03-Module 03-Lesson 02_SQL Joins/10. Video Alias.html 8.75 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/11. Video CAST.html 8.75 KB
Part 13-Module 01-Lesson 03_Udacity Professional Profile/03. Customizing Your Profile.html 8.75 KB
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2.html 8.74 KB
Part 18-Module 01-Lesson 04_Functions/08. Documentation.html 8.74 KB
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin.html 8.74 KB
Part 04-Module 01-Lesson 16_Logistic Regression/06. Video Interpreting Results - Part I.html 8.74 KB
Part 01-Module 02-Lesson 02_Explore Weather Trends/Project Description - Explore Weather Trends.html 8.74 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/04. Implementing the Program.html 8.74 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Video Data Types (Quantitative vs. Categorical).html 8.73 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/22. Solutions Percentiles.html 8.73 KB
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2.html 8.72 KB
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rule.html 8.72 KB
Part 18-Module 01-Lesson 05_Scripting/11. Errors and Exceptions.html 8.72 KB
Part 03-Module 01-Lesson 01_Anaconda/05. Managing environments.html 8.72 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/25. Congratulations and Next Steps.html 8.72 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Video Other Sampling Distributions.html 8.71 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/18. Video JOINing Subqueries.html 8.71 KB
Part 18-Module 01-Lesson 05_Scripting/20. Importing Files-qjeSn6zZbR0.ar.vtt 8.71 KB
Part 16-Module 01-Lesson 03_SVM/27. SVM Mini-Project.html 8.71 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles.html 8.7 KB
Part 04-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary.html 8.69 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/19. Query the Dataset 2.html 8.69 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size.html 8.69 KB
Part 16-Module 01-Lesson 12_Feature Selection/24. Overfitting a Decision Tree 2.html 8.69 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/Project Rubric - Technical Interview Practice.html 8.68 KB
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression.html 8.68 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Video Introduction to Notation.html 8.68 KB
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4.html 8.68 KB
Part 09-Module 01-Lesson 02_Design/09. Design Integrity.html 8.67 KB
Part 11-Module 01-Lesson 01_What is Version Control/01. What is Version Control.html 8.67 KB
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2.html 8.67 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/08. NumPy Matrix Multiplication.html 8.67 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/16. Building Program Pieces III.html 8.67 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.en.vtt 8.66 KB
Part 15-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier.html 8.65 KB
Part 04-Module 01-Lesson 16_Logistic Regression/33. Video Congratulations.html 8.65 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/13. Carat Frequency Polygon.html 8.65 KB
Part 16-Module 01-Lesson 12_Feature Selection/26. Accuracy of Your Overfit Decision Tree.html 8.64 KB
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3.html 8.64 KB
Part 16-Module 01-Lesson 14_Validation/17. Your First (Overfit) POI Identifier.html 8.64 KB
Part 16-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1.html 8.64 KB
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4.html 8.64 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study.html 8.63 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview.html 8.63 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/12. Dictionaries.html 8.63 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/09. Quiz Self JOINs.html 8.63 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/14. Bar Charts of Mean Price.html 8.62 KB
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8.html 8.62 KB
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7.html 8.62 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/27. Communicating Results Practice.html 8.62 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/28. Dict-to-array conversion.html 8.62 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/30. Missing POIs 2 (optional).html 8.61 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/05. Quiz Window Functions 2.html 8.61 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2-8jtk8BzBdj8.zh-CN.vtt 8.61 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/26. Unfilled Features.html 8.6 KB
Part 16-Module 01-Lesson 13_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.ar.vtt 8.59 KB
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1.html 8.59 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/06. Solutions Window Functions 2.html 8.58 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video.html 8.58 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/09. SQL Subquery Video-10pmKmTI_CA.pt-BR.vtt 8.58 KB
Part 04-Module 01-Lesson 14_Regression/06. Scatter Plots.html 8.58 KB
Part 16-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features.html 8.57 KB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4.html 8.57 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/03. Accuracy vs. Training Set Size.html 8.56 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/13. Video Dummy Variables Recap.html 8.56 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/06. Text General Notes for Building Data Dashboards with Trina.html 8.56 KB
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency.html 8.56 KB
Part 18-Module 01-Lesson 05_Scripting/07. Editing a Python Script.html 8.55 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/14. Features in the Enron Dataset.html 8.55 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/27. Text Recap.html 8.55 KB
Part 16-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video.html 8.55 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. Video JOINs with Comparison Operators.html 8.54 KB
Part 03-Module 03-Lesson 02_SQL Joins/07. Text Primary and Foreign Keys.html 8.54 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3.html 8.54 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/02. Text Optional Lessons Note.html 8.53 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/13. Gather (Summary).html 8.53 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/24. Enron CFO.html 8.53 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/01. Introduction.html 8.53 KB
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters.html 8.53 KB
Part 07-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations.html 8.53 KB
Part 04-Module 01-Lesson 07_Bayes Rule/29. Generalizing.html 8.52 KB
Part 16-Module 01-Lesson 09_Clustering/21. Clustering with 3 Features.html 8.52 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/22. Enron CEO.html 8.52 KB
Part 18-Module 01-Lesson 05_Scripting/16. Accessing Error Messages.html 8.51 KB
Part 08-Module 05-Lesson 01_Wrangle and Analyze Data/01. Project Overview.html 8.51 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/04. Write the Introduction.html 8.51 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/23. Enron Chairman.html 8.5 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/29. Hypothesis Testing Conclusion.html 8.5 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/24. Clean (Summary).html 8.5 KB
Part 09-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analyses.html 8.49 KB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2.html 8.49 KB
Part 04-Module 01-Lesson 14_Regression/10. Video What Defines A Line.html 8.48 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/02. Self-Practice Behavioral Questions.html 8.48 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/01. Diamonds.html 8.48 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2.html 8.48 KB
Part 16-Module 01-Lesson 12_Feature Selection/08. Features != Information.html 8.47 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum.html 8.47 KB
Part 18-Module 01-Lesson 03_Control Flow/34. Conclusion.html 8.46 KB
Part 08-Module 02-Lesson 01_Gathering Data/05. Source Files on Hand.html 8.46 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/06. Types of Errors - Part I.html 8.46 KB
Part 16-Module 01-Lesson 08_Outliers/12. Slope After Cleaning.html 8.45 KB
Part 07-Module 01-Lesson 03_Explore One Variable/01. Welcome!.html 8.45 KB
Part 18-Module 01-Lesson 05_Scripting/01. Introduction.html 8.45 KB
Part 16-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!.html 8.44 KB
Part 04-Module 01-Lesson 14_Regression/02. Video Introduction to Machine Learning.html 8.44 KB
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions.html 8.44 KB
Part 07-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size.html 8.44 KB
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3.html 8.43 KB
Part 16-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection.html 8.43 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots.html 8.43 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI.html 8.43 KB
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories.html 8.43 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/01. Video Introduction to Aggregation.html 8.43 KB
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition).html 8.43 KB
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric.html 8.43 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/03. Quiz Window Functions 1.html 8.42 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula.html 8.42 KB
Part 04-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics.html 8.42 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing.html 8.42 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/05. Video COUNT NULLs.html 8.42 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/15. What About with More Than Two Variables.html 8.42 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/05. DAP Overview-qdV4sifMmWI.pt-BR.vtt 8.42 KB
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6.html 8.41 KB
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5.html 8.41 KB
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4.html 8.41 KB
Part 16-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature.html 8.41 KB
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2.html 8.41 KB
Part 16-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye.html 8.41 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/22. Video HAVING.html 8.4 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/18. Solutions Comparing a Row to Previous Row.html 8.4 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data.html 8.4 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/04. Solutions LEFT RIGHT.html 8.4 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/08. Quiz ROW_NUMBER RANK.html 8.4 KB
Part 03-Module 01-Lesson 01_Anaconda/04. Managing packages.html 8.39 KB
Part 04-Module 01-Lesson 14_Regression/16. Video How to Interpret the Results.html 8.39 KB
Part 16-Module 01-Lesson 12_Feature Selection/16. Lasso Regression.html 8.39 KB
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1.html 8.39 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/03. Video Welcome!.html 8.38 KB
Part 16-Module 01-Lesson 12_Feature Selection/15. Regularization.html 8.37 KB
Part 08-Module 02-Lesson 01_Gathering Data/24. Other File Formats.html 8.37 KB
Part 04-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion.html 8.37 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3.html 8.36 KB
Part 04-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty.html 8.36 KB
Part 16-Module 01-Lesson 09_Clustering/22. Stock Option Range.html 8.36 KB
Part 07-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical of Outliers and Anomalies.html 8.36 KB
Part 11-Module 01-Lesson 06_Undoing Changes/03. Reverting A Commit.html 8.36 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Video Introduction to Summary Statistics.html 8.36 KB
Part 16-Module 01-Lesson 12_Feature Selection/22. Feature Selection Mini-Project.html 8.35 KB
Part 15-Module 02-Lesson 02_List-Based Collections/04. Python Lists.html 8.35 KB
Part 04-Module 01-Lesson 14_Regression/17. Video Does the Line Fit the Data Well.html 8.35 KB
Part 04-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data.html 8.34 KB
Part 07-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes.html 8.34 KB
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Part 04-Module 01-Lesson 11_Confidence Intervals/05. ScreenCast Difference In Means.html 8.33 KB
Part 15-Module 02-Lesson 06_Graphs/05. Graph Practice.html 8.33 KB
Part 07-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation.html 8.33 KB
Part 07-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width.html 8.32 KB
Part 16-Module 01-Lesson 11_Text Learning/19. Clean Away Signature Words.html 8.32 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3.html 8.31 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/03. Quiz LEFT RIGHT.html 8.31 KB
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Part 18-Module 01-Lesson 05_Scripting/21. The Standard Library.html 8.3 KB
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3.html 8.3 KB
Part 18-Module 01-Lesson 04_Functions/11. Lambda Expressions.html 8.3 KB
Part 09-Module 01-Lesson 02_Design/02. Lesson Overview.html 8.3 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/02. Video Introduction to NULLs.html 8.29 KB
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords.html 8.29 KB
Part 03-Module 03-Lesson 02_SQL Joins/15. Text Other JOIN Notes.html 8.29 KB
Part 08-Module 03-Lesson 01_Assessing Data/19. How Data Gets Dirty and Messy.html 8.28 KB
Part 16-Module 01-Lesson 09_Clustering/19. Clustering Features.html 8.28 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/07. Load Factor.html 8.28 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/12. Solutions Aggregates in Window Functions.html 8.28 KB
Part 08-Module 03-Lesson 01_Assessing Data/20. You Can Iterate!.html 8.28 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics.html 8.28 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge.html 8.27 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/09. Quiz CONCAT.html 8.27 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Introduce Instructors.html 8.26 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/14. Assessing and Building Intuition.html 8.26 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/20. Recap.html 8.26 KB
Part 08-Module 02-Lesson 01_Gathering Data/03. Dataset Finding the Best Movies.html 8.25 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/33. Text Recap.html 8.25 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/12. Video Other Language Associated with Confidence Intervals.html 8.25 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/02. AB Testing.html 8.25 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2.html 8.25 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/11. Interquartile Range - IQR.html 8.24 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/05. For Loops II.html 8.24 KB
Part 06-Module 02-Lesson 01_Statistics and Programming Exercises/05. Paired T-test Quiz.html 8.24 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/16. Gapminder Revisited.html 8.24 KB
Part 03-Module 03-Lesson 02_SQL Joins/05. Solution Your First JOIN.html 8.24 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/25. Smoothing Conditional Means.html 8.24 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited.html 8.23 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum.html 8.23 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Video Data Types Summary.html 8.23 KB
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Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/09. Solutions ROW_NUMBER RANK.html 8.23 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/04. Video What is Data Why is it important.html 8.23 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/04. Solutions Window Functions 1.html 8.22 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/03. Meet the Team.html 8.21 KB
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1.html 8.2 KB
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Part 03-Module 02-Lesson 01_The Data Analysis Process/13. Reading CSV Files.html 8.2 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax.html 8.2 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/18. Cleaning Practice.html 8.2 KB
Part 08-Module 03-Lesson 01_Assessing Data/02. Lesson Outline.html 8.2 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape.html 8.2 KB
Part 07-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots.html 8.2 KB
Part 16-Module 01-Lesson 09_Clustering/20. Deploying Clustering.html 8.2 KB
Part 12-Module 01-Lesson 01_GitHub Review/Project Description - Optimize Your GitHub Profile.html 8.17 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/02. Video From Sampling Distributions to Confidence Intervals.html 8.17 KB
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Part 07-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations.html 8.16 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/03. Screencast Fitting A Multiple Linear Regression Model.html 8.16 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/09. Statistical vs. Practical Significance.html 8.14 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data.html 8.14 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/13. Conclusions Visuals.html 8.14 KB
Part 16-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight.html 8.14 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/04. Solutions Write Your First Subquery.html 8.13 KB
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/11. Gapminder Multivariate Analysis.html 8.13 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/14. Video Correct Interpretations of Confidence Intervals.html 8.13 KB
Part 16-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn.html 8.13 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/03. Meet the Team.html 8.13 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4.html 8.13 KB
Part 07-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme.html 8.12 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/08. Video Statistical vs. Practical Significance.html 8.11 KB
Part 08-Module 04-Lesson 01_Cleaning Data/02. Lesson Outline.html 8.11 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/10. Solutions CONCAT.html 8.11 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/14. Your Udacity Professional Profile.html 8.11 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question.html 8.11 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps.html 8.1 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/22. Screencast How to Add Higher Order Terms.html 8.1 KB
Part 16-Module 01-Lesson 14_Validation/13. GridSearchCV in sklearn.html 8.09 KB
Part 09-Module 01-Lesson 02_Design/19. Same Data, Different Stories.html 8.09 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/12. Plot Colors for Qualitative Factors.html 8.09 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Video WITH.html 8.09 KB
Part 07-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer.html 8.08 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables.html 8.08 KB
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/05. Proportion of Friendships Initiated.html 8.08 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/04. Solutions FULL OUTER JOIN.html 8.08 KB
Part 03-Module 03-Lesson 02_SQL Joins/13. Video Motivation for Other JOINs.html 8.08 KB
Part 08-Module 02-Lesson 01_Gathering Data/20. Flashforward 2.html 8.07 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/18. Matplotlib Example.html 8.07 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/20. Video Higher Order Terms.html 8.07 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/05. DAP Overview-qdV4sifMmWI.en.vtt 8.06 KB
Part 18-Module 01-Lesson 05_Scripting/23. Solution The Standard Library.html 8.06 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/03. Binary Search Practice.html 8.06 KB
Part 01-Module 02-Lesson 02_Explore Weather Trends/01. Project Instructions.html 8.05 KB
Part 03-Module 04-Lesson 01_Investigate a Dataset/Project Description - Investigate a Dataset.html 8.05 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/Project Description - Technical Interview Practice.html 8.05 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions.html 8.05 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots.html 8.05 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias.html 8.05 KB
Part 16-Module 01-Lesson 09_Clustering/23. Salary Range.html 8.05 KB
Part 06-Module 02-Lesson 02_Test a Perceptual Phenomenon/04. Final Check of Instructions.html 8.04 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/11. Screencast Dummy Variables.html 8.04 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/05. Experiment I.html 8.04 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Video Aliases for Multiple Window Functions.html 8.04 KB
Part 15-Module 01-Lesson 05_Interview Practice/08. Keep Practicing!.html 8.04 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/20. Building the Linear Model.html 8.04 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/23. Video Interpreting Interactions.html 8.03 KB
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Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/14. Your Udacity Professional Profile.html 8.03 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/06. Cleaning Column Labels.html 8.03 KB
Part 13-Module 01-Lesson 03_Udacity Professional Profile/07. Projects.html 8.02 KB
Part 04-Module 01-Lesson 14_Regression/04. Video Introduction to Linear Regression.html 8.02 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/03. ScreenCast Sampling Distributions and Confidence Intervals.html 8.01 KB
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Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/06. The Rise of Diamonds.html 8.01 KB
Part 16-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron.html 8 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2.html 8 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting with Appending.html 8 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1.html 8 KB
Part 12-Module 01-Lesson 01_GitHub Review/17. Resources in Your Career Portal.html 8 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods.html 8 KB
Part 18-Module 01-Lesson 05_Scripting/15. Solution Handling Input Errors.html 7.99 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/16. Results with Merged Dataset.html 7.99 KB
Part 08-Module 02-Lesson 01_Gathering Data/11. Flashforward 1.html 7.99 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/15. Video Potential Problems.html 7.99 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/11. ScreenCast Traditional Confidence Interval Methods.html 7.99 KB
Part 04-Module 02-Lesson 01_Analyze AB Test Results/03. Quiz 2 Messy Data.html 7.98 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/07. Solutions JOINs with Comparison Operators.html 7.97 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data.html 7.96 KB
Part 16-Module 01-Lesson 10_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.ar.vtt 7.96 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/05. Git Diff.html 7.96 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation.html 7.96 KB
Part 18-Module 01-Lesson 05_Scripting/29. Conclusion.html 7.96 KB
Part 07-Module 01-Lesson 01_What is EDA/02. Data is Ubiquitous.html 7.95 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.en.vtt 7.95 KB
Part 04-Module 01-Lesson 14_Regression/15. Screencast Fitting A Regression Line in Python.html 7.95 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/24. Final Thoughts.html 7.94 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads.html 7.93 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/01. Welcome!.html 7.93 KB
Part 08-Module 02-Lesson 01_Gathering Data/19. Mashup Solution.html 7.92 KB
Part 04-Module 01-Lesson 14_Regression/22. Text Recap + Next Steps.html 7.92 KB
Part 04-Module 01-Lesson 04_Probability/20. Text Recap + Next Steps.html 7.92 KB
Part 02-Module 01-Lesson 04_Files and Modules/04. Variable Scope.html 7.92 KB
Part 16-Module 01-Lesson 11_Text Learning/17. Warming Up with parseOutText().html 7.92 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads.html 7.92 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads.html 7.91 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.pt-BR.vtt 7.91 KB
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Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3.html 7.91 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/Project Description - Craft Your Cover Letter.html 7.91 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/05. Video POSITION, STRPOS, SUBSTR.html 7.91 KB
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Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/10. Solutions Self JOINs.html 7.9 KB
Part 09-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings.html 7.89 KB
Part 04-Module 01-Lesson 14_Regression/13. Video Fitting A Regression Line.html 7.89 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2.html 7.88 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/10. Price Box Plots.html 7.88 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/12. Price per Carat Box Plots by Color.html 7.88 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula.html 7.88 KB
Part 18-Module 01-Lesson 04_Functions/04. Solution Defining Functions.html 7.88 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/04. Errors.html 7.87 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation.html 7.87 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements.html 7.87 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/20. Type Quality Plot with Matplotlib.html 7.86 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/02. Video + Text What's Ahead.html 7.86 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example.html 7.85 KB
Part 12-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2.html 7.85 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/06. Video More On Subqueries.html 7.85 KB
Part 16-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2.html 7.85 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/01. Handoff to Juno Lee.html 7.85 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/13. Solutions UNION.html 7.85 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails.html 7.85 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4.html 7.84 KB
Part 08-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate.html 7.84 KB
Part 07-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-v4UGBUB6jO4.ar.vtt 7.84 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example.html 7.84 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data with Visuals.html 7.84 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6.html 7.83 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5.html 7.83 KB
Part 07-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes.html 7.83 KB
Part 13-Module 01-Lesson 03_Udacity Professional Profile/04. Top Section.html 7.83 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3.html 7.83 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/03. Lists II.html 7.83 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4.html 7.83 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios.html 7.82 KB
Part 16-Module 01-Lesson 08_Outliers/14. Enron Outliers.html 7.81 KB
Part 07-Module 01-Lesson 03_Explore One Variable/02. What to Do First.html 7.81 KB
Part 16-Module 01-Lesson 08_Outliers/10. Slope of Regression with Outliers.html 7.8 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial.html 7.8 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/07. Video Confidence Interval Applications.html 7.8 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling and EDA.html 7.8 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/10. Scatterplot Transformation.html 7.8 KB
Part 03-Module 03-Lesson 02_SQL Joins/18. Video JOINs and Filtering.html 7.8 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results.html 7.79 KB
Part 09-Module 01-Lesson 02_Design/14. Designing for Color Blindness.html 7.79 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/24. Many Variables.html 7.79 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/11. Time for Live Practice with Pramp.html 7.79 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/10. Creating a slideshow.html 7.79 KB
Part 04-Module 02-Lesson 01_Analyze AB Test Results/Project Rubric - Analyze AB Test Results.html 7.79 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability.html 7.79 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/20. Plotting with Pandas.html 7.78 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/08. Click Through Rate.html 7.78 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions.html 7.78 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/08. Solutions More On Subqueries.html 7.77 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/17. Video + Text Recap.html 7.76 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. Projects.html 7.76 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/17. Cleaning Example-7bnSPYtPDzQ.pt-BR.vtt 7.76 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/07. Resume Review (Prior Industry Experience).html 7.76 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/17. Text Recap + Next Steps.html 7.76 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/04. David's Data Wrangling Example-TN-CWy3GK44.pt-BR.vtt 7.76 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/17. Cleaning Example.html 7.75 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/09. Fixing Data Types Pt 1.html 7.75 KB
Part 16-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn-aCdg-d_476Y.ar.vtt 7.74 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/09. Bubble Sort Practice.html 7.74 KB
Part 18-Module 01-Lesson 04_Functions/16. [Optional] Solution Iterators and Generators.html 7.73 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/04. David's Data Wrangling Example-TN-CWy3GK44.en.vtt 7.73 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/12. Merge Sort Practice.html 7.73 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data.html 7.73 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.zh-CN.vtt 7.72 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/01. Welcome!.html 7.72 KB
Part 16-Module 01-Lesson 11_Text Learning/18. Deploying Stemming.html 7.72 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction.html 7.72 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/11. How Do I Find Time for My Nanodegree.html 7.72 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose.html 7.72 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/08. Integrity and Mindset.html 7.71 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion.html 7.71 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview.html 7.7 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/13. Solutions CAST.html 7.69 KB
Part 09-Module 01-Lesson 02_Design/16. General Design Tips.html 7.69 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Video Introduction to Window Functions.html 7.69 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value.html 7.69 KB
Part 06-Module 02-Lesson 02_Test a Perceptual Phenomenon/Project Rubric - Test a Perceptual Phenomenon.html 7.68 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value.html 7.68 KB
Part 04-Module 01-Lesson 14_Regression/01. Video Introduction.html 7.68 KB
Part 03-Module 03-Lesson 02_SQL Joins/03. Video Introduction to JOINs.html 7.68 KB
Part 07-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac.html 7.68 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Video Aggregates in Window Functions.html 7.68 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/07. Resume Review (Career Change).html 7.68 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/09. Price per Carat by Cut.html 7.67 KB
Part 16-Module 01-Lesson 14_Validation/18. Deploying a TrainingTesting Regime.html 7.67 KB
Part 04-Module 02-Lesson 01_Analyze AB Test Results/Project Description - Analyze AB Test Results.html 7.67 KB
Part 16-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-GdsLRKjjKLw.ar.vtt 7.67 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/06. Quiz POSITION, STRPOS, SUBSTR - AME DATA AS QUIZ 1.html 7.66 KB
Part 09-Module 01-Lesson 02_Design/21. Recap.html 7.66 KB
Part 16-Module 01-Lesson 07_Regressions/index.html 7.66 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Video Introduction to Percentiles.html 7.65 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather (CSV Files).html 7.65 KB
Part 15-Module 02-Lesson 02_List-Based Collections/12. Queue Practice.html 7.65 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/12. Adjustments - price vs. volume.html 7.65 KB
Part 12-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages.html 7.64 KB
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/06. prop_initiated vs. tenure.html 7.64 KB
Part 16-Module 01-Lesson 08_Outliers/17. Any More Outliers.html 7.64 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/10. How Do I Find Time for My Nanodegree.html 7.64 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/05. Cheaper Diamonds.html 7.64 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/07. Integrity and Mindset.html 7.63 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review.html 7.63 KB
Part 16-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn-COVRSk0GDEE.ar.vtt 7.63 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data.html 7.63 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Video ROW_NUMBER RANK.html 7.62 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather (Intro).html 7.62 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/07. Resume Review (Entry-level).html 7.62 KB
Part 16-Module 01-Lesson 10_Feature Scaling/17. When to Deploy Feature Scaling.html 7.61 KB
Part 08-Module 02-Lesson 01_Gathering Data/25. You Can Iterate.html 7.61 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Video Recap.html 7.61 KB
Part 16-Module 01-Lesson 11_Text Learning/20. TfIdf It.html 7.6 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion.html 7.6 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/08. Coding 2-qEteyPNRSwU.en.vtt 7.6 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (After Cleaning)-OF2486euiRE.ar.vtt 7.59 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots.html 7.59 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/14. Types of Merges.html 7.59 KB
Part 08-Module 02-Lesson 01_Gathering Data/01. Introduction.html 7.59 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/09. Solution Video More On Subqueries.html 7.59 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/05. Adjustments - price vs. depth.html 7.59 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.zh-CN.vtt 7.59 KB
Part 08-Module 03-Lesson 01_Assessing Data/21. Assessing Summary.html 7.59 KB
Part 08-Module 02-Lesson 01_Gathering Data/26. Gathering Summary.html 7.59 KB
Part 15-Module 02-Lesson 05_Trees/04. Tree Practice.html 7.58 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/02. Video LEFT RIGHT.html 7.58 KB
Part 08-Module 02-Lesson 01_Gathering Data/27. Conclusion.html 7.57 KB
Part 18-Module 01-Lesson 04_Functions/09. Quiz Documentation.html 7.57 KB
Part 09-Module 01-Lesson 02_Design/05. What Makes a Bad Visual.html 7.57 KB
Part 08-Module 05-Lesson 01_Wrangle and Analyze Data/Project Description - Wrangle and Analyze Data.html 7.57 KB
Part 08-Module 03-Lesson 01_Assessing Data/09. Quality Visual Assessment 1 -XfKc5PtJ7cc.en.vtt 7.56 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation.html 7.54 KB
Part 08-Module 03-Lesson 01_Assessing Data/08. Visual Assessment Acquaint Yourself.html 7.54 KB
Part 08-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 1-nDWAZOU3W3U.pt-BR.vtt 7.54 KB
Part 03-Module 01-Lesson 01_Anaconda/03. Installing Anaconda.html 7.54 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions.html 7.54 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/01. Video Introduction.html 7.53 KB
Part 06-Module 02-Lesson 02_Test a Perceptual Phenomenon/01. Project Overview.html 7.53 KB
Part 16-Module 01-Lesson 08_Outliers/19. Remove These Outliers.html 7.52 KB
Part 09-Module 01-Lesson 02_Design/08. Data Ink Ratio-gW2FapuYV4A.ar.vtt 7.52 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/07. Appending Data.html 7.5 KB
Part 16-Module 01-Lesson 08_Outliers/18. Identifying Two More Outliers.html 7.49 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration.html 7.48 KB
Part 16-Module 01-Lesson 09_Clustering/18. K-Means Clustering Mini-Project.html 7.48 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-FC_GNjqj5zI.ja.vtt 7.48 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending and NumPy.html 7.48 KB
Part 09-Module 01-Lesson 02_Design/07. Chart Junk.html 7.47 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/15. Dictionaries IV.html 7.47 KB
Part 09-Module 01-Lesson 02_Design/12. Text Effective Explanatory Visual Recap.html 7.47 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/25. Smoothing Conditional Means-hxk2cgdChUw.ar.vtt 7.46 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/05. DAP Overview-qdV4sifMmWI.zh-CN.vtt 7.46 KB
Part 16-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn.html 7.46 KB
Part 06-Module 02-Lesson 01_Statistics and Programming Exercises/08. Date Projection.html 7.46 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations.html 7.46 KB
Part 09-Module 01-Lesson 02_Design/13. Using Color.html 7.45 KB
Part 06-Module 02-Lesson 01_Statistics and Programming Exercises/07. Most Frequent Word.html 7.45 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate.html 7.44 KB
Part 08-Module 03-Lesson 01_Assessing Data/01. Introduction.html 7.44 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/16. Video Subquery Conclusion.html 7.44 KB
Part 16-Module 01-Lesson 13_PCA/29. When to Use PCA-hJZHcmJBk1o.ar.vtt 7.44 KB
Part 03-Module 02-Lesson 04_Programming Workflow for Data Analysis/03. Scripting Your Analysis.html 7.43 KB
Part 16-Module 01-Lesson 10_Feature Scaling/16. Computing Rescaled Features.html 7.42 KB
Part 16-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3.html 7.42 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components.html 7.42 KB
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/04. Price vs. Volume and Diamond Clarity.html 7.41 KB
Part 08-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 1-nDWAZOU3W3U.en.vtt 7.41 KB
Part 16-Module 01-Lesson 08_Outliers/16. Remove Enron Outlier.html 7.41 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/index.html 7.41 KB
Part 08-Module 03-Lesson 01_Assessing Data/22. Conclusion.html 7.4 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/13. Resources in Your Career Portal.html 7.4 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/07. Solutions POSITION, STRPOS, SUBSTR.html 7.39 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/13. Meet the Careers Team.html 7.39 KB
Part 03-Module 04-Lesson 01_Investigate a Dataset/01. Project Overview.html 7.39 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview.html 7.39 KB
Part 18-Module 01-Lesson 04_Functions/07. Solution Variable Scope.html 7.38 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/02. Linear Regression Models.html 7.38 KB
Part 12-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects.html 7.38 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/01. Case Study Introduction.html 7.36 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/09. Experiment II.html 7.36 KB
Part 16-Module 01-Lesson 04_Decision Trees/index.html 7.36 KB
Part 16-Module 01-Lesson 09_Clustering/13. Some challenges of k-means.html 7.36 KB
Part 09-Module 01-Lesson 02_Design/08. Data Ink Ratio.html 7.35 KB
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/01. Price Histograms with Facet and Color.html 7.35 KB
Part 18-Module 01-Lesson 05_Scripting/20. Importing Files-qjeSn6zZbR0.pt-BR.vtt 7.35 KB
Part 18-Module 01-Lesson 04_Functions/10. Solution Documentation.html 7.34 KB
Part 18-Module 01-Lesson 04_Functions/18. Conclusion.html 7.34 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots.html 7.32 KB
Part 04-Module 01-Lesson 14_Regression/21. Video Recap.html 7.32 KB
Part 16-Module 01-Lesson 09_Clustering/01. Unsupervised Learning.html 7.32 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview.html 7.32 KB
Part 16-Module 01-Lesson 08_Outliers/15. Identify the Biggest Enron Outlier.html 7.31 KB
Part 07-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.ar.vtt 7.31 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/12. Meet the Careers Team.html 7.31 KB
Part 09-Module 02-Lesson 01_Create a Tableau Story/Project Description - Create a Tableau Story.html 7.31 KB
Part 16-Module 01-Lesson 11_Text Learning/21. Accessing TfIdf Features.html 7.3 KB
Part 16-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn.html 7.3 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type Quality Plot - Part 1.html 7.3 KB
Part 12-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items.html 7.3 KB
Part 18-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.pt-BR.vtt 7.29 KB
Part 03-Module 03-Lesson 01_Basic SQL/index.html 7.29 KB
Part 02-Module 02-Lesson 01_Python Project/02. Project Details.html 7.29 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/index.html 7.29 KB
Part 16-Module 01-Lesson 09_Clustering/02. Clustering Movies.html 7.29 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/16. Video Confidence Intervals Hypothesis Tests.html 7.29 KB
Part 12-Module 01-Lesson 01_GitHub Review/01. Introduction.html 7.29 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/14. Pandas Query.html 7.29 KB
Part 16-Module 01-Lesson 09_Clustering/08. Handoff to Katie.html 7.28 KB
Part 16-Module 01-Lesson 02_Naive Bayes/index.html 7.28 KB
Part 12-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter.html 7.28 KB
Part 08-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty vs. Messy 1.html 7.28 KB
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/10. PriceCarat Binned, Faceted, Colored.html 7.28 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/07. Coding-zhQYREUI8Z0.pt-BR.vtt 7.27 KB
Part 08-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1-5UYGvKDsd-M.pt-BR.vtt 7.27 KB
Part 09-Module 01-Lesson 02_Design/18. Tell A Story.html 7.26 KB
Part 08-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.en.vtt 7.26 KB
Part 08-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.en.vtt 7.26 KB
Part 06-Module 02-Lesson 02_Test a Perceptual Phenomenon/Project Description - Test a Perceptual Phenomenon.html 7.25 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/08. Video Self JOINs.html 7.25 KB
Part 16-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video.html 7.25 KB
Part 08-Module 04-Lesson 01_Cleaning Data/20. Conclusion.html 7.24 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/17. Cleaning Example-7bnSPYtPDzQ.en.vtt 7.24 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/09. price vs. volume.html 7.23 KB
Part 18-Module 01-Lesson 04_Functions/01. Introduction.html 7.23 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/01. Video Communicating With Your Data.html 7.23 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview.html 7.22 KB
Part 16-Module 01-Lesson 02_Naive Bayes/01. ML in The Google Self-Driving Car-lL16AQItG1g.ar.vtt 7.21 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/13. Access Your Career Portal.html 7.21 KB
Part 08-Module 03-Lesson 01_Assessing Data/07. Visual Assessment.html 7.21 KB
Part 16-Module 01-Lesson 09_Clustering/12. Sklearn.html 7.21 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby.html 7.21 KB
Part 16-Module 01-Lesson 11_Text Learning/16. Text Learning Mini-Project.html 7.21 KB
Part 16-Module 01-Lesson 10_Feature Scaling/15. What Kind of Scaling.html 7.2 KB
Part 18-Module 01-Lesson 04_Functions/06. Variable Scope.html 7.2 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/04. Business Example.html 7.2 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.ar.vtt 7.2 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/index.html 7.2 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/09. Iterative Programming III.html 7.2 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/01. Video Introduction.html 7.19 KB
Part 07-Module 02-Lesson 01_Explore and Summarize Data/04. Evaluation and Submission.html 7.19 KB
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/02. Price vs. Table Colored by Cut.html 7.19 KB
Part 08-Module 04-Lesson 01_Cleaning Data/08. Address Missing Data First.html 7.19 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/19. Plotting with Matplotlib.html 7.18 KB
Part 08-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1-5UYGvKDsd-M.en.vtt 7.18 KB
Part 07-Module 01-Lesson 01_What is EDA/03. Go Exploring.html 7.17 KB
Part 18-Module 01-Lesson 04_Functions/13. Solution Lambda Expressions.html 7.17 KB
Part 07-Module 01-Lesson 02_R Basics/10. Read and Subset Data-UdniaeLsViQ.ja.vtt 7.16 KB
Part 16-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy.html 7.15 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/03. Video Hierarchies with Trina.html 7.15 KB
Part 16-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary.html 7.15 KB
Part 03-Module 03-Lesson 02_SQL Joins/01. Video Motivation.html 7.14 KB
Part 07-Module 01-Lesson 02_R Basics/15. Data Munging.html 7.14 KB
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes.html 7.14 KB
Part 16-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video.html 7.13 KB
Part 12-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2.html 7.13 KB
Part 08-Module 03-Lesson 01_Assessing Data/09. Quality Visual Assessment 1 -XfKc5PtJ7cc.pt-BR.vtt 7.12 KB
Part 07-Module 01-Lesson 02_R Basics/09. Getting Help.html 7.12 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/img/resid-plots.gif 7.11 KB
Part 16-Module 01-Lesson 02_Naive Bayes/18. Gaussian NB Example-wpnDwiqTCJA.ar.vtt 7.1 KB
Part 08-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.pt-BR.vtt 7.1 KB
Part 08-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.pt-BR.vtt 7.1 KB
Part 15-Module 01-Lesson 05_Interview Practice/09. Resources in Your Career Portal.html 7.1 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/01. Data Visualization Introduction.html 7.09 KB
Part 16-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning.html 7.09 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/07. Correlation - price and depth.html 7.08 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Conclusion.html 7.07 KB
Part 16-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit.html 7.07 KB
Part 12-Module 01-Lesson 01_GitHub Review/16. Outro.html 7.07 KB
Part 16-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words.html 7.06 KB
Part 04-Module 01-Lesson 06_Conditional Probability/16. Text Summary.html 7.06 KB
Part 16-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project.html 7.06 KB
Part 04-Module 02-Lesson 01_Analyze AB Test Results/07. Completing and Submitting this Project in the Classroom.html 7.05 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/14. Video COALESCE.html 7.05 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/08. Resources in Your Career Portal.html 7.05 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/11. Code with Branches V.html 7.05 KB
Part 16-Module 01-Lesson 13_PCA/28. PCA in sklearn-SBYdqlLgbGk.ar.vtt 7.05 KB
Part 08-Module 04-Lesson 01_Cleaning Data/10. Solution Missing Data.html 7.05 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2.html 7.05 KB
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/11. Correlations on Subsets.html 7.04 KB
Part 07-Module 01-Lesson 02_R Basics/10. Read and Subset Data.html 7.04 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/01. Video Introduction to SQL Data Cleaning.html 7.04 KB
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Part 03-Module 01-Lesson 01_Anaconda/06. More environment actions.html 7.04 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/14. Video Performance Tuning Motivation.html 7.04 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion.html 7.04 KB
Part 12-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2.html 7.03 KB
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Part 12-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1.html 7.03 KB
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Part 16-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK.html 7.02 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/02. Video Introduction to Subqueries.html 7.02 KB
Part 16-Module 01-Lesson 08_Outliers/11. Score of Regression with Outliers.html 7.01 KB
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Part 12-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository.html 6.99 KB
Part 07-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows.html 6.99 KB
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Part 09-Module 01-Lesson 02_Design/01. Introduction.html 6.98 KB
Part 07-Module 01-Lesson 02_R Basics/12. Factor Variables.html 6.98 KB
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Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/08. Resources in Your Career Portal.html 6.97 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/16. Video Performance Tuning 2.html 6.97 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/17. Video Performance Tuning 3.html 6.96 KB
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Part 09-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next.html 6.95 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/09. Converting notebooks.html 6.95 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/08. Video CONCAT.html 6.95 KB
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Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/index.html 6.95 KB
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Part 18-Module 01-Lesson 02_Data Types and Operators/index.html 6.95 KB
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Part 09-Module 02-Lesson 01_Create a Tableau Story/01. Project Overview.html 6.92 KB
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Part 12-Module 01-Lesson 01_GitHub Review/06. Quick Fixes #1.html 6.91 KB
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Part 16-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video.html 6.9 KB
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable/04. Diamond Counts.html 6.9 KB
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Part 16-Module 01-Lesson 13_PCA/index.html 6.89 KB
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Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables/08. price vs. carat.html 6.88 KB
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Part 13-Module 01-Lesson 03_Udacity Professional Profile/Project Description - Udacity Professional Profile Review.html 6.86 KB
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Part 01-Module 02-Lesson 02_Explore Weather Trends/02. Accessing Data With SQL.html 6.82 KB
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Part 03-Module 01-Lesson 01_Anaconda/08. Python Versions.html 6.82 KB
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Part 08-Module 04-Lesson 01_Cleaning Data/11. Cleaning for Tidiness.html 6.77 KB
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Part 07-Module 01-Lesson 01_What is EDA/04. Why learn EDA.html 6.77 KB
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Part 18-Module 01-Lesson 04_Functions/17. [Optional] Generator Expressions.html 6.76 KB
Part 07-Module 01-Lesson 02_R Basics/06. Ready to Explore Data.html 6.76 KB
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Part 07-Module 02-Lesson 01_Explore and Summarize Data/03. Project Template RMD File.html 6.76 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/17. Compound Data Structures II.html 6.75 KB
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Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences.html 6.34 KB
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Part 06-Module 01-Lesson 01_Welcome to Term 2!/06. Orientation Introduction.html 6.31 KB
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Part 06-Module 02-Lesson 01_Statistics and Programming Exercises/04. Football Statistics.html 6.28 KB
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Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/06. Projects and Progress.html 6.27 KB
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Part 07-Module 01-Lesson 01_What is EDA/08. Our Approach for This Course.html 6.27 KB
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Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/02. Projects.html 6.24 KB
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Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely.html 6.1 KB
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Part 06-Module 02-Lesson 01_Statistics and Programming Exercises/02. Socks from a Box.html 5.98 KB
Part 02-Module 01-Lesson 04_Files and Modules/08. The Standard Library II.html 5.97 KB
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Part 16-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites.html 5.93 KB
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Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options.html 5.84 KB
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Part 18-Module 01-Lesson 01_Why Python Programming/02. Welcome to the Course!.html 5.83 KB
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Part 15-Module 01-Lesson 02_Practice Behavioral Questions/01. Introduction.html 5.82 KB
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Part 14-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose of the Cover Letter.html 5.81 KB
Part 05-Module 01-Lesson 01_Congratulations & Next Steps/01. Congratulations Next Steps.html 5.81 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/index.html 5.8 KB
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Part 02-Module 02-Lesson 01_Python Project/08. Project Walkthrough.html 5.79 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/01. Congratulations!.html 5.78 KB
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Part 07-Module 01-Lesson 01_What is EDA/09. Aude Explores Coordinated Migration-7ihp6ofAJG8.en.vtt 4.61 KB
Part 16-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-GdsLRKjjKLw.zh-CN.vtt 4.61 KB
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Part 04-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.th.vtt 4.6 KB
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.ar.vtt 4.59 KB
Part 12-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.ar.vtt 4.59 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.ar.vtt 4.58 KB
Part 08-Module 02-Lesson 01_Gathering Data/06. Flat File Structure-bLKVRIhrZUY.zh-CN.vtt 4.58 KB
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Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2-ZXy8jgywY5g.zh-CN.vtt 4.57 KB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.ar.vtt 4.57 KB
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Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables/index.html 4.56 KB
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Part 04-Module 01-Lesson 06_Conditional Probability/index.html 4.56 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.zh-CN.vtt 4.55 KB
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Part 15-Module 02-Lesson 03_Searching and Sorting/index.html 4.53 KB
Part 01-Module 01-Lesson 02_The Life of a Data Analyst/03. Industry Interview Sinthuja-R5XBQ7dSz7w.zh-CN.vtt 4.53 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 26 Branching Overview-ywcOC6CLG4s.zh-CN.vtt 4.53 KB
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Part 15-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort-kUon6854joI.pt-BR.vtt 4.53 KB
Part 07-Module 01-Lesson 01_What is EDA/09. Aude Explores Coordinated Migration-7ihp6ofAJG8.ja.vtt 4.53 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.ar.vtt 4.53 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.ar.vtt 4.52 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort-kUon6854joI.zh-CN.vtt 4.52 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.pt-BR.vtt 4.52 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.es-MX.vtt 4.52 KB
Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.pt-BR.vtt 4.51 KB
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.ar.vtt 4.51 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/index.html 4.51 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.ar.vtt 4.51 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/index.html 4.51 KB
Part 15-Module 01-Lesson 05_Interview Practice/index.html 4.5 KB
Part 16-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.pt-BR.vtt 4.5 KB
Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.en.vtt 4.5 KB
Part 18-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.ar.vtt 4.5 KB
Part 09-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.ar.vtt 4.49 KB
Part 04-Module 02-Lesson 01_Analyze AB Test Results/index.html 4.49 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.zh-CN.vtt 4.49 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.ar.vtt 4.48 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.ar.vtt 4.48 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.en.vtt 4.47 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.en.vtt 4.47 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.pt-BR.vtt 4.47 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/06. A Problem and How You Dealt With It-7IKqdW30GvQ.zh-CN.vtt 4.47 KB
Part 07-Module 01-Lesson 01_What is EDA/04. Why learn EDA-YM68DrqJw1I.pt-BR.vtt 4.47 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.ar.vtt 4.46 KB
Part 07-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.zh-CN.vtt 4.46 KB
Part 03-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.ar.vtt 4.45 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.ar.vtt 4.45 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/09. SELECT FROM Statements-urOYuuav4BY.ar.vtt 4.45 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.pt-BR.vtt 4.45 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Using Python to get HTML-1Y_CZyKNWe4.ar.vtt 4.44 KB
Part 18-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.pt-BR.vtt 4.43 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.ja.vtt 4.42 KB
Part 18-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.ar.vtt 4.42 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.en-US.vtt 4.42 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.en.vtt 4.42 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/index.html 4.41 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/index.html 4.41 KB
Part 08-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.zh-CN.vtt 4.41 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.zh-CN.vtt 4.41 KB
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.ar.vtt 4.41 KB
Part 16-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.pt-BR.vtt 4.4 KB
Part 16-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn-COVRSk0GDEE.zh-CN.vtt 4.4 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/index.html 4.4 KB
Part 16-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.en.vtt 4.4 KB
Part 16-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.ar.vtt 4.39 KB
Part 16-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.pt-BR.vtt 4.39 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/05. How Does MLR Work-bvM6eUYyurA.zh-CN.vtt 4.38 KB
Part 07-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.ja.vtt 4.37 KB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.pt-BR.vtt 4.37 KB
Part 08-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.ar.vtt 4.37 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/index.html 4.37 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/29. 11 CASE V2-BInXuTY_FzE.zh-CN.vtt 4.37 KB
Part 08-Module 02-Lesson 01_Gathering Data/16. JSON File Structure-hO2CayzZBoA.zh-CN.vtt 4.37 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.ar.vtt 4.37 KB
Part 16-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.ar.vtt 4.36 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.ar.vtt 4.36 KB
Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.ar.vtt 4.36 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.ar.vtt 4.35 KB
Part 16-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-4GBJk6R0pb4.zh-CN.vtt 4.35 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/index.html 4.34 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.en.vtt 4.34 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/22. Looking at Samples of Households-kQePh6UTB90.pt-BR.vtt 4.34 KB
Part 18-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.en.vtt 4.34 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/22. L2 09 Lists And Membership Operators V2-rNV_E50wcWM.pt-BR.vtt 4.34 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.ar.vtt 4.33 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/index.html 4.33 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/index.html 4.33 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.pt-BR.vtt 4.32 KB
Part 13-Module 01-Lesson 03_Udacity Professional Profile/index.html 4.32 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.pt-BR.vtt 4.32 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/index.html 4.32 KB
Part 16-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.ar.vtt 4.31 KB
Part 15-Module 02-Lesson 06_Graphs/index.html 4.31 KB
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.ar.vtt 4.3 KB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.ar.vtt 4.3 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.en.vtt 4.3 KB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.ar.vtt 4.3 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.ar.vtt 4.3 KB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.ar.vtt 4.3 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Do Analysts Like SQL-uCNOtUht2Xc.ar.vtt 4.3 KB
Part 07-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.ar.vtt 4.29 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question-xQJyObqxg3E.pt-BR.vtt 4.29 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/01. Ud1110 IntroPy L5 01 A Wikipedia Crawl-osrplIl1m-k.pt-BR.vtt 4.29 KB
Part 08-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.ar.vtt 4.28 KB
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.ar.vtt 4.27 KB
Part 03-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.en.vtt 4.27 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.zh-CN.vtt 4.26 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Beautiful Soup Demonstration-dk7ESZXLnk4.ar.vtt 4.26 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/index.html 4.25 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/01. Ud1110 IntroPy L5 01 A Wikipedia Crawl-osrplIl1m-k.en.vtt 4.25 KB
Part 07-Module 01-Lesson 01_What is EDA/04. Why learn EDA-YM68DrqJw1I.en.vtt 4.25 KB
Part 09-Module 01-Lesson 02_Design/09. Design Integrity-y72_fVFtqlY.pt-BR.vtt 4.24 KB
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.en.vtt 4.24 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import-tU1N-8aNB_M.pt-BR.vtt 4.23 KB
Part 07-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.ar.vtt 4.23 KB
Part 15-Module 02-Lesson 02_List-Based Collections/03. Arrays-OnPP5xDmFv0.pt-BR.vtt 4.23 KB
Part 09-Module 01-Lesson 02_Design/13. Using Color-6bAedqD3ilw.zh-CN.vtt 4.23 KB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.en-US.vtt 4.23 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/index.html 4.22 KB
Part 15-Module 01-Lesson 05_Interview Practice/04. Query a SQL database-UVSFLWdAKl4.zh-CN.vtt 4.22 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/index.html 4.22 KB
Part 07-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.ar.vtt 4.22 KB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.en.vtt 4.22 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.en-US.vtt 4.22 KB
Part 09-Module 01-Lesson 02_Design/09. Design Integrity-y72_fVFtqlY.en.vtt 4.22 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.pt-BR.vtt 4.22 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/index.html 4.21 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.en.vtt 4.21 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.pt-BR.vtt 4.21 KB
Part 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.pt-BR.vtt 4.2 KB
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.ar.vtt 4.2 KB
Part 07-Module 01-Lesson 01_What is EDA/index.html 4.2 KB
Part 02-Module 02-Lesson 01_Python Project/index.html 4.2 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.en.vtt 4.19 KB
Part 15-Module 02-Lesson 02_List-Based Collections/index.html 4.19 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/20. Notation for Random Variables-8NxTW1u4s-Y.zh-CN.vtt 4.18 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/01. Ud1110 IntroPy L5 01 A Wikipedia Crawl-osrplIl1m-k.zh-CN.vtt 4.18 KB
Part 08-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.ar.vtt 4.18 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/16. What Is A P-value Anyway-eU6pUZjqviA.pt-BR.vtt 4.18 KB
Part 09-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.pt-BR.vtt 4.18 KB
Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.ja.vtt 4.18 KB
Part 15-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.en-US.vtt 4.17 KB
Part 15-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.en.vtt 4.17 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.zh-CN.vtt 4.17 KB
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.ar.vtt 4.17 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.ar.vtt 4.17 KB
Part 16-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.pt-BR.vtt 4.17 KB
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.ar.vtt 4.16 KB
Part 16-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.ar.vtt 4.16 KB
Part 18-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.pt-BR.vtt 4.15 KB
Part 16-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.en.vtt 4.15 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-28iU6GrDVfU.en.vtt 4.15 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.ar.vtt 4.14 KB
Part 18-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.en.vtt 4.14 KB
Part 02-Module 01-Lesson 04_Files and Modules/index.html 4.14 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.ar.vtt 4.13 KB
Part 07-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.pt-BR.vtt 4.13 KB
Part 01-Module 01-Lesson 02_The Life of a Data Analyst/04. Lada's Money Bag Meme - Data Analysis with R-Isa_FGQrvgs.pt-BR.vtt 4.13 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/01. A Repository's History - Intro-UBmg3syQS0E.pt-BR.vtt 4.13 KB
Part 07-Module 02-Lesson 01_Explore and Summarize Data/index.html 4.13 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.pt-BR.vtt 4.13 KB
Part 18-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.ar.vtt 4.13 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/01. Welcome To DAND Term 1-Q1GEXzXXLN0.ar.vtt 4.13 KB
Part 16-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.en-US.vtt 4.12 KB
Part 15-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.en-US.vtt 4.12 KB
Part 03-Module 04-Lesson 01_Investigate a Dataset/index.html 4.12 KB
Part 15-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.en.vtt 4.12 KB
Part 18-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.ar.vtt 4.12 KB
Part 16-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.en.vtt 4.12 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.zh-CN.vtt 4.11 KB
Part 06-Module 02-Lesson 02_Test a Perceptual Phenomenon/index.html 4.11 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.en.vtt 4.11 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.ar.vtt 4.11 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.pt-BR.vtt 4.1 KB
Part 12-Module 01-Lesson 01_GitHub Review/13. Interview with Art - Part 3-M6PKr3S1rPg.en.vtt 4.1 KB
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.ar.vtt 4.1 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/index.html 4.09 KB
Part 16-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.en.vtt 4.09 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import-tU1N-8aNB_M.en.vtt 4.09 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.ar.vtt 4.09 KB
Part 15-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.en-US.vtt 4.09 KB
Part 04-Module 01-Lesson 08_Python Probability Practice/index.html 4.08 KB
Part 15-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.en.vtt 4.08 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/index.html 4.08 KB
Part 07-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.zh-CN.vtt 4.08 KB
Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.zh-CN.vtt 4.08 KB
Part 16-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.ar.vtt 4.07 KB
Part 16-Module 01-Lesson 07_Regressions/31. R Squared in SKlearn-Dxf1I4IE6co.zh-CN.vtt 4.07 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.pt-BR.vtt 4.07 KB
Part 16-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.en.vtt 4.06 KB
Part 06-Module 02-Lesson 01_Statistics and Programming Exercises/index.html 4.06 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.ar.vtt 4.06 KB
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Part 03-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.en.vtt 3.49 KB
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Part 15-Module 01-Lesson 04_Land a Job Offer/index.html 3.47 KB
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Part 13-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.pt-BR.vtt 3.47 KB
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Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.en.vtt 3.46 KB
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Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.en.vtt 3.46 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.ar.vtt 3.46 KB
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Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.it.vtt 3.45 KB
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Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Using Python to get HTML-1Y_CZyKNWe4.pt-BR.vtt 3.44 KB
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Part 03-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.en.vtt 3.44 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.en.vtt 3.44 KB
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Part 18-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.ar.vtt 3.43 KB
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Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Using Python to get HTML-1Y_CZyKNWe4.en.vtt 3.43 KB
Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.zh-CN.vtt 3.43 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.pt-BR.vtt 3.43 KB
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Part 16-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.zh-CN.vtt 3.42 KB
Part 18-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.ar.vtt 3.42 KB
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Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 15 Git The Big Picture-dVil8e0yptQ.pt-BR.vtt 3.41 KB
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.es-ES.vtt 3.41 KB
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Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 43 Case Study Review-jiZwuN6zTFs.ar.vtt 3.41 KB
Part 07-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.pt-BR.vtt 3.41 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.pt-BR.vtt 3.41 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.zh-CN.vtt 3.4 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.ar.vtt 3.4 KB
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Part 13-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.en.vtt 3.4 KB
Part 12-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.zh-CN.vtt 3.4 KB
Part 15-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.pt-BR.vtt 3.4 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. Kaggle Project Final For Classroom-Ssttix340C8.en.vtt 3.4 KB
Part 18-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.pt-BR.vtt 3.39 KB
Part 04-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.pt-BR.vtt 3.39 KB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.pt-BR.vtt 3.39 KB
Part 16-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.pt-BR.vtt 3.39 KB
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Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.en.vtt 3.37 KB
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-GuBics_6HOk.ar.vtt 3.37 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.ar.vtt 3.36 KB
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Part 16-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.zh-CN.vtt 3.36 KB
Part 16-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.ja.vtt 3.36 KB
Part 16-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.zh-CN.vtt 3.36 KB
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Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.th.vtt 3.35 KB
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Part 03-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.en.vtt 3.34 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/09. SELECT FROM Statements-urOYuuav4BY.en.vtt 3.34 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.en.vtt 3.34 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.ar.vtt 3.34 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.ar.vtt 3.34 KB
Part 16-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.ar.vtt 3.34 KB
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.ar.vtt 3.33 KB
Part 01-Module 01-Lesson 02_The Life of a Data Analyst/02. Interview with a Data Scientist-kNnFA5hxI2Q.zh-CN.vtt 3.33 KB
Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.en.vtt 3.33 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.ar.vtt 3.32 KB
Part 09-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.en.vtt 3.32 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.en.vtt 3.32 KB
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.en.vtt 3.32 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.pt-BR.vtt 3.31 KB
Part 04-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.pt-BR.vtt 3.31 KB
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.en.vtt 3.31 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.en.vtt 3.31 KB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.ar.vtt 3.31 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 15 Git The Big Picture-dVil8e0yptQ.zh-CN.vtt 3.31 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/14. Simulating From the Null-sL2yJtHZd8Y.en.vtt 3.31 KB
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.ja.vtt 3.31 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.zh-CN.vtt 3.31 KB
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.en.vtt 3.31 KB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.ar.vtt 3.3 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Using Python to get HTML-1Y_CZyKNWe4.zh-CN.vtt 3.3 KB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.ar.vtt 3.3 KB
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.pt-BR.vtt 3.3 KB
Part 07-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.zh-CN.vtt 3.3 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.ar.vtt 3.29 KB
Part 16-Module 01-Lesson 07_Regressions/27. Problem with Minimizing Absolute Errors-U46D7oEijlI.zh-CN.vtt 3.29 KB
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.pt-BR.vtt 3.29 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.pt-BR.vtt 3.29 KB
Part 15-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.en-US.vtt 3.29 KB
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.ja.vtt 3.29 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.zh-CN.vtt 3.29 KB
Part 18-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.zh-CN.vtt 3.29 KB
Part 15-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.en.vtt 3.29 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.ar.vtt 3.29 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.en-US.vtt 3.29 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.ar.vtt 3.29 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.ar.vtt 3.29 KB
Part 08-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.en.vtt 3.28 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.en.vtt 3.28 KB
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.en.vtt 3.28 KB
Part 11-Module 01-Lesson 01_What is Version Control/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 30 Configure Terminal-CCYjHfBk9hw.ar.vtt 3.28 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.ar.vtt 3.28 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.en.vtt 3.28 KB
Part 18-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.pt-BR.vtt 3.28 KB
Part 09-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.ar.vtt 3.28 KB
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.ar.vtt 3.28 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.ja.vtt 3.28 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.pt-BR.vtt 3.28 KB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.pt-BR.vtt 3.28 KB
Part 16-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.zh-CN.vtt 3.27 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.pt-BR.vtt 3.27 KB
Part 07-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.zh-CN.vtt 3.27 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/14. Simulating From the Null-sL2yJtHZd8Y.pt-BR.vtt 3.27 KB
Part 16-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.pt-BR.vtt 3.27 KB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.ar.vtt 3.27 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.ar.vtt 3.27 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.pt-BR.vtt 3.27 KB
Part 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.ar.vtt 3.27 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.zh-CN.vtt 3.26 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.zh-CN.vtt 3.26 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.zh-CN.vtt 3.26 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.pt-BR.vtt 3.26 KB
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.pt-BR.vtt 3.26 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.zh-CN.vtt 3.26 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.en.vtt 3.25 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 34 Finding The First Link 2-bsMtF-705EU.ar.vtt 3.25 KB
Part 15-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.en-US.vtt 3.25 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.en.vtt 3.25 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Do Analysts Like SQL-uCNOtUht2Xc.pt-BR.vtt 3.25 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.pt-BR.vtt 3.25 KB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.pt-BR.vtt 3.25 KB
Part 15-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.en.vtt 3.25 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.ar.vtt 3.25 KB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.th.vtt 3.25 KB
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.pt-BR.vtt 3.24 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.ar.vtt 3.24 KB
Part 16-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.ar.vtt 3.24 KB
Part 08-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces) 2-tobH58uO24U.zh-CN.vtt 3.23 KB
Part 03-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.pt-BR.vtt 3.23 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.ar.vtt 3.23 KB
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.pt-BR.vtt 3.23 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.pt-BR.vtt 3.23 KB
Part 04-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.en.vtt 3.23 KB
Part 01-Module 01-Lesson 02_The Life of a Data Analyst/01. Sparta Science-MkjoaUmdOXc.pt-BR.vtt 3.22 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.en.vtt 3.22 KB
Part 16-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.en.vtt 3.22 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.en.vtt 3.22 KB
Part 09-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.zh-CN.vtt 3.22 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.es-MX.vtt 3.22 KB
Part 07-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.en.vtt 3.21 KB
Part 03-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.zh-CN.vtt 3.21 KB
Part 16-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.ja.vtt 3.21 KB
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.pt-BR.vtt 3.21 KB
Part 16-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.en.vtt 3.21 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.en.vtt 3.21 KB
Part 16-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.ar.vtt 3.21 KB
Part 07-Module 01-Lesson 01_What is EDA/02. Data is Ubiquitous-YbVuN2KOlt4.zh-CN.vtt 3.21 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.es-MX.vtt 3.2 KB
Part 15-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.en-US.vtt 3.2 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.ar.vtt 3.2 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.pt-BR.vtt 3.2 KB
Part 11-Module 01-Lesson 01_What is Version Control/01. Gitfinal L1 01 Welcome-lbR82UD5F0c.zh-CN.vtt 3.2 KB
Part 15-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.en.vtt 3.2 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function-iJEBxsKDDoE.pt-BR.vtt 3.2 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.pt-BR.vtt 3.2 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.pt-BR.vtt 3.2 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.pt-BR.vtt 3.19 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.pt-BR.vtt 3.19 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.pt-BR.vtt 3.19 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.zh-CN.vtt 3.19 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.en.vtt 3.19 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.ar.vtt 3.19 KB
Part 18-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.pt-BR.vtt 3.18 KB
Part 08-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.en.vtt 3.18 KB
Part 04-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.zh-CN.vtt 3.18 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.pt-BR.vtt 3.18 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/41. AND BETWEEN Operators-nBuDPneWcKY.ar.vtt 3.17 KB
Part 03-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.ar.vtt 3.17 KB
Part 16-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.en.vtt 3.17 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.pt-BR.vtt 3.17 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.en.vtt 3.17 KB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.en.vtt 3.17 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.en-US.vtt 3.17 KB
Part 16-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.en.vtt 3.17 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.en-US.vtt 3.17 KB
Part 04-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.pt-BR.vtt 3.17 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.en.vtt 3.17 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.ar.vtt 3.17 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.ar.vtt 3.16 KB
Part 08-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.en.vtt 3.16 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.en.vtt 3.16 KB
Part 15-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.en-US.vtt 3.16 KB
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.pt-BR.vtt 3.16 KB
Part 15-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.en.vtt 3.16 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/24. What If Our Sample Is Large-WoTCeSTL1eM.en.vtt 3.16 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.zh-CN.vtt 3.16 KB
Part 15-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.pt-BR.vtt 3.16 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.pt-BR.vtt 3.15 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.pt-BR.vtt 3.15 KB
Part 16-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.ar.vtt 3.15 KB
Part 16-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.pt-BR.vtt 3.15 KB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.ar.vtt 3.15 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.en.vtt 3.14 KB
Part 12-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.pt-BR.vtt 3.14 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.pt-BR.vtt 3.14 KB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.ja.vtt 3.14 KB
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.ar.vtt 3.13 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.ar.vtt 3.13 KB
Part 16-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.pt-BR.vtt 3.13 KB
Part 07-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.ja.vtt 3.13 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.zh-CN.vtt 3.13 KB
Part 16-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.zh-CN.vtt 3.13 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.en.vtt 3.13 KB
Part 15-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.en.vtt 3.13 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.en.vtt 3.13 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.en.vtt 3.12 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.ar.vtt 3.12 KB
Part 07-Module 01-Lesson 01_What is EDA/06. Goals of EDA-NEvuulahg2g.ja.vtt 3.12 KB
Part 07-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.pt-BR.vtt 3.12 KB
Part 15-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.pt-BR.vtt 3.12 KB
Part 16-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.pt-BR.vtt 3.12 KB
Part 15-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.pt-BR.vtt 3.12 KB
Part 08-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.en.vtt 3.12 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.ar.vtt 3.11 KB
Part 09-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.zh-CN.vtt 3.11 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/08. Types Of Errors - Part II-mbdSQ5CjdFs.en.vtt 3.11 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.pt-BR.vtt 3.11 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.zh-CN.vtt 3.11 KB
Part 01-Module 01-Lesson 02_The Life of a Data Analyst/01. Sparta Science-MkjoaUmdOXc.en.vtt 3.11 KB
Part 15-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.en.vtt 3.11 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.zh-CN.vtt 3.11 KB
Part 18-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.pt-BR.vtt 3.11 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/38. NOT Operator-dSQF87oW8a0.ar.vtt 3.1 KB
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.pt-BR.vtt 3.1 KB
Part 03-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.ar.vtt 3.1 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.en.vtt 3.1 KB
Part 07-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.ar.vtt 3.1 KB
Part 18-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.zh-CN.vtt 3.1 KB
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.zh-CN.vtt 3.09 KB
Part 16-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.en.vtt 3.09 KB
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.pt-BR.vtt 3.08 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.en.vtt 3.08 KB
Part 07-Module 01-Lesson 01_What is EDA/06. Goals of EDA-NEvuulahg2g.pt-BR.vtt 3.08 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.zh-CN.vtt 3.08 KB
Part 03-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.zh-CN.vtt 3.08 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/09. SELECT FROM Statements-urOYuuav4BY.zh-CN.vtt 3.08 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.ar.vtt 3.08 KB
Part 03-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.ar.vtt 3.08 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.en.vtt 3.08 KB
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Part 02-Module 01-Lesson 03_Data Structures and Loops/18. Problem Solving Skills-el9knzvU4TM.pt-BR.vtt 3.08 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/01. Welcome To DAND Term 1-Q1GEXzXXLN0.pt-BR.vtt 3.08 KB
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.ja.vtt 3.08 KB
Part 18-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.en.vtt 3.08 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function-iJEBxsKDDoE.en.vtt 3.08 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.zh-CN.vtt 3.07 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.ar.vtt 3.07 KB
Part 04-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.ar.vtt 3.07 KB
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.en.vtt 3.07 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.pt-BR.vtt 3.07 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.pt-BR.vtt 3.07 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Beautiful Soup Demonstration-dk7ESZXLnk4.en.vtt 3.07 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.zh-CN.vtt 3.07 KB
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.ja.vtt 3.07 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.zh-CN.vtt 3.07 KB
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.pt-BR.vtt 3.07 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.ar.vtt 3.07 KB
Part 07-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.ar.vtt 3.07 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.en.vtt 3.07 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Beautiful Soup Demonstration-dk7ESZXLnk4.zh-CN.vtt 3.07 KB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.zh-CN.vtt 3.07 KB
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.en.vtt 3.07 KB
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.ar.vtt 3.07 KB
Part 09-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.zh-CN.vtt 3.06 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.ar.vtt 3.06 KB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.ar.vtt 3.06 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Businesses Choose Databases-j4ey7--h9r8.ar.vtt 3.06 KB
Part 08-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.pt-BR.vtt 3.06 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.zh-CN.vtt 3.06 KB
Part 04-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.en.vtt 3.06 KB
Part 16-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.ar.vtt 3.05 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.pt-BR.vtt 3.05 KB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.en.vtt 3.05 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.zh-CN.vtt 3.05 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.ar.vtt 3.05 KB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.en.vtt 3.05 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Beautiful Soup Demonstration-dk7ESZXLnk4.pt-BR.vtt 3.05 KB
Part 15-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.zh-CN.vtt 3.05 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.ar.vtt 3.05 KB
Part 16-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.en.vtt 3.04 KB
Part 08-Module 03-Lesson 01_Assessing Data/07. Visual Assessment -GVVibuIg3Ro.zh-CN.vtt 3.04 KB
Part 16-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.zh-CN.vtt 3.04 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.zh-CN.vtt 3.04 KB
Part 18-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.en.vtt 3.04 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/06. Dynamic Programming-VQeFcG9pjJU.zh-CN.vtt 3.04 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.ar.vtt 3.04 KB
Part 07-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.en.vtt 3.04 KB
Part 04-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.en.vtt 3.03 KB
Part 07-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.en.vtt 3.03 KB
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.en.vtt 3.03 KB
Part 18-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.pt-BR.vtt 3.03 KB
Part 16-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.pt-BR.vtt 3.03 KB
Part 18-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.pt-BR.vtt 3.03 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.ar.vtt 3.03 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.en-US.vtt 3.03 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/01. Welcome To DAND Term 1-Q1GEXzXXLN0.en.vtt 3.03 KB
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.ar.vtt 3.03 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.pt-BR.vtt 3.03 KB
Part 16-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.ar.vtt 3.03 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.en.vtt 3.03 KB
Part 08-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.zh-CN.vtt 3.02 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.en.vtt 3.02 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.pt-BR.vtt 3.02 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/24. What If Our Sample Is Large-WoTCeSTL1eM.pt-BR.vtt 3.02 KB
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.ar.vtt 3.02 KB
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.it.vtt 3.02 KB
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Part 15-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.zh-CN.vtt 3.02 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.en.vtt 3.01 KB
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.pt-BR.vtt 3.01 KB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.ar.vtt 3.01 KB
Part 04-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.zh-CN.vtt 3.01 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.en.vtt 3.01 KB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.ja.vtt 3.01 KB
Part 16-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.ar.vtt 3.01 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.ar.vtt 3 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.ar.vtt 3 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson-nWFJ_eOU27I.zh-CN.vtt 3 KB
Part 07-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.ja.vtt 3 KB
Part 04-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.pt-BR.vtt 3 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.ar.vtt 3 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/22. WHERE Statements -mN0uTnlXaxg.ar.vtt 3 KB
Part 03-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.ar.vtt 3 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.pt-BR.vtt 3 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.zh-CN.vtt 2.99 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/08. Types Of Errors - Part II-mbdSQ5CjdFs.pt-BR.vtt 2.99 KB
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.es-ES.vtt 2.99 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.en.vtt 2.99 KB
Part 08-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.pt-BR.vtt 2.99 KB
Part 16-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.ar.vtt 2.99 KB
Part 16-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.zh-CN.vtt 2.99 KB
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.zh-CN.vtt 2.99 KB
Part 07-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.pt-BR.vtt 2.98 KB
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.en.vtt 2.98 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.en.vtt 2.98 KB
Part 18-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.ar.vtt 2.98 KB
Part 16-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.en.vtt 2.98 KB
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.th.vtt 2.98 KB
Part 18-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.pt-BR.vtt 2.97 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.zh-CN.vtt 2.97 KB
Part 09-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.ar.vtt 2.97 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.ar.vtt 2.97 KB
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Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.zh-CN.vtt 2.97 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Standard Deviation Calculation-H5zA1A-XPoY.zh-CN.vtt 2.97 KB
Part 11-Module 01-Lesson 01_What is Version Control/01. Gitfinal L1 03 Version Control Systems-b7TjsVoTo3Q.ar.vtt 2.97 KB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.en.vtt 2.97 KB
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.ar.vtt 2.96 KB
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Part 04-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.pt-BR.vtt 2.96 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.ja.vtt 2.96 KB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.ar.vtt 2.96 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.ar.vtt 2.96 KB
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Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.en.vtt 2.96 KB
Part 15-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.pt-BR.vtt 2.96 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.pt-BR.vtt 2.96 KB
Part 16-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.ar.vtt 2.95 KB
Part 16-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.en.vtt 2.95 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/22. L2 08 Lists And Membership Operators V2-JAbZdZg5_x8.pt-BR.vtt 2.95 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.ar.vtt 2.95 KB
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.en.vtt 2.95 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.zh-CN.vtt 2.95 KB
Part 08-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.zh-CN.vtt 2.95 KB
Part 08-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.en.vtt 2.95 KB
Part 07-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.zh-CN.vtt 2.94 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.en.vtt 2.94 KB
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.zh-CN.vtt 2.94 KB
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Part 04-Module 01-Lesson 12_Hypothesis Testing/10. Types Of Errors - Part III-Z-srkCPsdaM.pt-BR.vtt 2.94 KB
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Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.pt-BR.vtt 2.94 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.pt-BR.vtt 2.93 KB
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Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Continue Crawl Solution-cFwJ_MO3ofs.ar.vtt 2.93 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.en.vtt 2.93 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.en.vtt 2.93 KB
Part 12-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.en.vtt 2.93 KB
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.ar.vtt 2.93 KB
Part 18-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.en.vtt 2.93 KB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.zh-CN.vtt 2.92 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.pt-BR.vtt 2.92 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate-EpfoKAwV_Eg.zh-CN.vtt 2.92 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.en.vtt 2.92 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.en.vtt 2.92 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.ar.vtt 2.92 KB
Part 07-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.ar.vtt 2.92 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.pt-BR.vtt 2.92 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.en.vtt 2.92 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.ar.vtt 2.92 KB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.en.vtt 2.92 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.pt-BR.vtt 2.91 KB
Part 07-Module 01-Lesson 01_What is EDA/06. Goals of EDA-NEvuulahg2g.en.vtt 2.91 KB
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.th.vtt 2.91 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/10. Types Of Errors - Part III-Z-srkCPsdaM.en.vtt 2.9 KB
Part 16-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.ja.vtt 2.9 KB
Part 15-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.zh-CN.vtt 2.9 KB
Part 15-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.zh-CN.vtt 2.9 KB
Part 07-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.zh-CN.vtt 2.9 KB
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.ar.vtt 2.9 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.zh-CN.vtt 2.9 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.en.vtt 2.9 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.en.vtt 2.9 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 43 Case Study Review-jiZwuN6zTFs.pt-BR.vtt 2.9 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.pt-BR.vtt 2.89 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. Kaggle Project Final For Classroom-Ssttix340C8.pt-BR.vtt 2.89 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.en.vtt 2.89 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.en.vtt 2.89 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.ar.vtt 2.89 KB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.ar.vtt 2.89 KB
Part 16-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.ar.vtt 2.89 KB
Part 18-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.zh-CN.vtt 2.88 KB
Part 07-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.ar.vtt 2.88 KB
Part 08-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.zh-CN.vtt 2.88 KB
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Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.ar.vtt 2.88 KB
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Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/08. Self JOINs-tw_VzEGBOvI.ar.vtt 2.88 KB
Part 16-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.en.vtt 2.87 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.pt-BR.vtt 2.87 KB
Part 04-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.it.vtt 2.87 KB
Part 08-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.pt-BR.vtt 2.87 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Do Analysts Like SQL-uCNOtUht2Xc.en.vtt 2.87 KB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.en.vtt 2.87 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.en.vtt 2.87 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.zh-CN.vtt 2.87 KB
Part 16-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.pt-BR.vtt 2.87 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.pt-BR.vtt 2.87 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.en.vtt 2.86 KB
Part 16-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.ar.vtt 2.86 KB
Part 16-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.ja.vtt 2.86 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/17. Calculating the p-value-_W3Jg7jQ8jI.zh-CN.vtt 2.86 KB
Part 18-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.ar.vtt 2.86 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.ja.vtt 2.86 KB
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.zh-CN.vtt 2.86 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.pt-BR.vtt 2.86 KB
Part 08-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.pt-BR.vtt 2.86 KB
Part 15-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.en-US.vtt 2.86 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.en.vtt 2.86 KB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.ar.vtt 2.86 KB
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.ja.vtt 2.86 KB
Part 15-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.en.vtt 2.86 KB
Part 07-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.ja.vtt 2.86 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.zh-CN.vtt 2.85 KB
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.en.vtt 2.85 KB
Part 16-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.en.vtt 2.84 KB
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.zh-CN.vtt 2.84 KB
Part 09-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.ar.vtt 2.84 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.th.vtt 2.84 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.pt-BR.vtt 2.84 KB
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.ja.vtt 2.84 KB
Part 04-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.es-ES.vtt 2.84 KB
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.en.vtt 2.84 KB
Part 18-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.en.vtt 2.83 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.pt-BR.vtt 2.83 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.pt-BR.vtt 2.83 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.zh-CN.vtt 2.83 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.en.vtt 2.83 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.zh-CN.vtt 2.83 KB
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.en.vtt 2.83 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.pt-BR.vtt 2.83 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.zh-CN.vtt 2.83 KB
Part 15-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.zh-CN.vtt 2.83 KB
Part 04-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.pt-BR.vtt 2.82 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.pt-BR.vtt 2.82 KB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.zh-CN.vtt 2.82 KB
Part 16-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.pt-BR.vtt 2.82 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.pt-BR.vtt 2.82 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.pt-BR.vtt 2.82 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.en.vtt 2.82 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.pt-BR.vtt 2.82 KB
Part 03-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.ar.vtt 2.82 KB
Part 12-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.ar.vtt 2.82 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/44. OR Operator-3vLGEuXAAvA.ar.vtt 2.82 KB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.ar.vtt 2.82 KB
Part 08-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.zh-CN.vtt 2.82 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/06. Ud1110 IntroPy L218 My Python Programming Setup-wrnov8J5zto.en.vtt 2.82 KB
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.pt-BR.vtt 2.82 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.ar.vtt 2.81 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.zh-CN.vtt 2.81 KB
Part 15-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.zh-CN.vtt 2.81 KB
Part 16-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.ar.vtt 2.81 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/18. Problem Solving Skills-el9knzvU4TM.en.vtt 2.81 KB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.zh-CN.vtt 2.81 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.pt-BR.vtt 2.81 KB
Part 16-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.ar.vtt 2.81 KB
Part 18-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.zh-CN.vtt 2.81 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.ar.vtt 2.8 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.ar.vtt 2.8 KB
Part 07-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.ar.vtt 2.8 KB
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.ja.vtt 2.8 KB
Part 11-Module 01-Lesson 06_Undoing Changes/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L6 17 Soft Vs Medium Vs Hard Walkthrough-UN7ki2G2yKc.en.vtt 2.8 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.pt-BR.vtt 2.8 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.pt-BR.vtt 2.8 KB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.pt-BR.vtt 2.8 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.pt-BR.vtt 2.8 KB
Part 08-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.en.vtt 2.79 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.ar.vtt 2.79 KB
Part 16-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.pt-BR.vtt 2.79 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/04. Setting Up Hypotheses - Part II-nByvHz77GiA.pt-BR.vtt 2.79 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Gitfinal L1 13 Git'S Terminology-bf26adzeqMM.pt-BR.vtt 2.79 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.pt-BR.vtt 2.79 KB
Part 16-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.en.vtt 2.79 KB
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.pt-BR.vtt 2.79 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.zh-CN.vtt 2.79 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.zh-CN.vtt 2.79 KB
Part 16-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.en.vtt 2.79 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/01. Welcome To DAND Term 1-Q1GEXzXXLN0.zh-CN.vtt 2.79 KB
Part 07-Module 01-Lesson 01_What is EDA/03. Go Exploring-dias-YUpewk.ar.vtt 2.79 KB
Part 16-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.en.vtt 2.78 KB
Part 18-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.en.vtt 2.78 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.pt-BR.vtt 2.78 KB
Part 08-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.ar.vtt 2.78 KB
Part 16-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.ar.vtt 2.78 KB
Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.zh-CN.vtt 2.77 KB
Part 16-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.en.vtt 2.77 KB
Part 08-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.en.vtt 2.77 KB
Part 16-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.pt-BR.vtt 2.77 KB
Part 16-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.en.vtt 2.77 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/02. What's Ahead-ggbCydfI1JM.ar.vtt 2.77 KB
Part 15-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.pt-BR.vtt 2.77 KB
Part 16-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.en.vtt 2.77 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/24. What If Our Sample Is Large-WoTCeSTL1eM.zh-CN.vtt 2.76 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/19. Order By Part II-XQCjREdOqwE.ar.vtt 2.76 KB
Part 03-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.ar.vtt 2.76 KB
Part 16-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.pt-BR.vtt 2.76 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.pt-BR.vtt 2.76 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.zh-CN.vtt 2.76 KB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.zh-CN.vtt 2.76 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Do Analysts Like SQL-uCNOtUht2Xc.zh-CN.vtt 2.76 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/31. L2 02 Dictionaries And Identiy Operators V3-QR8HTxCTWi0.zh-CN.vtt 2.76 KB
Part 11-Module 01-Lesson 01_What is Version Control/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 30 Configure Terminal-CCYjHfBk9hw.pt-BR.vtt 2.76 KB
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.pt-BR.vtt 2.75 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.en.vtt 2.75 KB
Part 16-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.zh-CN.vtt 2.75 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/11. Time Commitment-d-VfUw7wNEQ.ar.vtt 2.75 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/10. Time Commitment-d-VfUw7wNEQ.ar.vtt 2.75 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.en-US.vtt 2.75 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.en.vtt 2.75 KB
Part 07-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.zh-CN.vtt 2.75 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.en.vtt 2.75 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.ja.vtt 2.75 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.en.vtt 2.75 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.en.vtt 2.75 KB
Part 08-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.zh-CN.vtt 2.74 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.zh-CN.vtt 2.74 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.zh-CN.vtt 2.74 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.es-MX.vtt 2.74 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.en.vtt 2.74 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.ja.vtt 2.74 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.es-MX.vtt 2.74 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.es-MX.vtt 2.74 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.en.vtt 2.74 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.es-MX.vtt 2.74 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.pt-BR.vtt 2.74 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.ja.vtt 2.74 KB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.ja.vtt 2.74 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.en.vtt 2.74 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.zh-CN.vtt 2.74 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.pt-BR.vtt 2.74 KB
Part 18-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.zh-CN.vtt 2.73 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.ar.vtt 2.73 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.pt-BR.vtt 2.73 KB
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.ja.vtt 2.73 KB
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.th.vtt 2.73 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.en.vtt 2.73 KB
Part 16-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.zh-CN.vtt 2.73 KB
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.ar.vtt 2.73 KB
Part 18-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.en.vtt 2.73 KB
Part 18-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.ar.vtt 2.72 KB
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.ar.vtt 2.72 KB
Part 07-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.ja.vtt 2.72 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/13. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.pt-BR.vtt 2.72 KB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.zh-CN.vtt 2.72 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/02. DSND Trailer Final-X2xQnb-bR8A.pt-BR.vtt 2.72 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.zh-CN.vtt 2.72 KB
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.en.vtt 2.72 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.pt-BR.vtt 2.71 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.es-MX.vtt 2.71 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.ar.vtt 2.71 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.ar.vtt 2.71 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/04. Setting Up Hypotheses - Part II-nByvHz77GiA.en.vtt 2.71 KB
Part 04-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.zh-CN.vtt 2.71 KB
Part 18-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.en.vtt 2.7 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.zh-CN.vtt 2.7 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.pt-BR.vtt 2.7 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.pt-BR.vtt 2.7 KB
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Part 18-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.en.vtt 2.7 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.zh-CN.vtt 2.7 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/14. Simulating From the Null-sL2yJtHZd8Y.zh-CN.vtt 2.7 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.pt-BR.vtt 2.7 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.en.vtt 2.7 KB
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Part 07-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.pt-BR.vtt 2.7 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/22. WHERE Statements -mN0uTnlXaxg.pt-BR.vtt 2.7 KB
Part 03-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.pt-BR.vtt 2.7 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.pt-BR.vtt 2.69 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.en.vtt 2.69 KB
Part 07-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.ar.vtt 2.69 KB
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.pt-BR.vtt 2.69 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.zh-CN.vtt 2.69 KB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.pt-BR.vtt 2.69 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.en.vtt 2.69 KB
Part 08-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.pt-BR.vtt 2.68 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.pt-BR.vtt 2.68 KB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.pt-BR.vtt 2.68 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Businesses Choose Databases-j4ey7--h9r8.pt-BR.vtt 2.68 KB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.ar.vtt 2.68 KB
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.zh-CN.vtt 2.68 KB
Part 18-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.pt-BR.vtt 2.68 KB
Part 08-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.pt-BR.vtt 2.68 KB
Part 15-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.en-US.vtt 2.68 KB
Part 04-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.es-ES.vtt 2.68 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function-iJEBxsKDDoE.zh-CN.vtt 2.68 KB
Part 16-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.ar.vtt 2.68 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.en.vtt 2.68 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.zh-CN.vtt 2.68 KB
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.zh-CN.vtt 2.68 KB
Part 15-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.en.vtt 2.67 KB
Part 04-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.pt-BR.vtt 2.67 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 43 Case Study Review-jiZwuN6zTFs.en.vtt 2.67 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.ar.vtt 2.67 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.ar.vtt 2.67 KB
Part 11-Module 01-Lesson 06_Undoing Changes/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L6 17 Soft Vs Medium Vs Hard Walkthrough-UN7ki2G2yKc.pt-BR.vtt 2.67 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Exploring HTML with Developer Tools-YWbCvLCBQrg.pt-BR.vtt 2.67 KB
Part 16-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.zh-CN.vtt 2.67 KB
Part 18-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.en.vtt 2.67 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. What are we going to do-rK6YlbBiKQM.ar.vtt 2.67 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.en.vtt 2.67 KB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.ja.vtt 2.67 KB
Part 08-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.ar.vtt 2.67 KB
Part 16-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.zh-CN.vtt 2.66 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/32. LIKE Operator-O5z6eWkNip4.ar.vtt 2.66 KB
Part 03-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.ar.vtt 2.66 KB
Part 07-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.zh-CN.vtt 2.66 KB
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.ar.vtt 2.66 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.zh-CN.vtt 2.66 KB
Part 15-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.pt-BR.vtt 2.66 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.pt-BR.vtt 2.66 KB
Part 04-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.en.vtt 2.66 KB
Part 16-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.pt-BR.vtt 2.66 KB
Part 15-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.pt-BR.vtt 2.65 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.pt-BR.vtt 2.65 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.ja.vtt 2.65 KB
Part 15-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.en.vtt 2.65 KB
Part 12-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.zh-CN.vtt 2.65 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.en.vtt 2.65 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.ar.vtt 2.65 KB
Part 15-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.en-US.vtt 2.65 KB
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.en.vtt 2.65 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.zh-CN.vtt 2.65 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.pt-BR.vtt 2.65 KB
Part 15-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.en.vtt 2.65 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.ar.vtt 2.65 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Gitfinal L1 13 Git'S Terminology-bf26adzeqMM.en.vtt 2.65 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.pt-BR.vtt 2.64 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/06. Ud1110 IntroPy L218 My Python Programming Setup-wrnov8J5zto.pt-BR.vtt 2.64 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/13. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.en.vtt 2.64 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.en.vtt 2.64 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.en.vtt 2.64 KB
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.zh-CN.vtt 2.64 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/01. Jupyter-qiYDWFLyXvg.zh-CN.vtt 2.64 KB
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.ar.vtt 2.64 KB
Part 16-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.pt-BR.vtt 2.64 KB
Part 08-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.zh-CN.vtt 2.64 KB
Part 07-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.pt-BR.vtt 2.64 KB
Part 04-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.ja.vtt 2.63 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.ar.vtt 2.63 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.en.vtt 2.63 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.ar.vtt 2.63 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.pt-BR.vtt 2.63 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.en.vtt 2.63 KB
Part 16-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.pt-BR.vtt 2.63 KB
Part 08-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.ar.vtt 2.63 KB
Part 04-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.en.vtt 2.63 KB
Part 16-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.zh-CN.vtt 2.63 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.es-MX.vtt 2.63 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.en.vtt 2.63 KB
Part 18-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.pt-BR.vtt 2.63 KB
Part 08-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.zh-CN.vtt 2.63 KB
Part 03-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.ar.vtt 2.63 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.pt-BR.vtt 2.63 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.zh-CN.vtt 2.63 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.en.vtt 2.62 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/01. Welcome!-KJT4Z0xpHns.ar.vtt 2.62 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.pt-BR.vtt 2.62 KB
Part 04-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.zh-CN.vtt 2.62 KB
Part 16-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.ar.vtt 2.62 KB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.zh-CN.vtt 2.62 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.zh-CN.vtt 2.62 KB
Part 04-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.pt-BR.vtt 2.62 KB
Part 16-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.pt-BR.vtt 2.62 KB
Part 04-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.en.vtt 2.61 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.ar.vtt 2.61 KB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.ar.vtt 2.61 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.ar.vtt 2.61 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.zh-CN.vtt 2.61 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.pt-BR.vtt 2.61 KB
Part 09-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.pt-BR.vtt 2.61 KB
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-GuBics_6HOk.ja.vtt 2.61 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.pt-BR.vtt 2.61 KB
Part 12-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.ar.vtt 2.61 KB
Part 07-Module 01-Lesson 01_What is EDA/06. Goals of EDA-NEvuulahg2g.zh-CN.vtt 2.61 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.ar.vtt 2.6 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.ar.vtt 2.6 KB
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.zh-CN.vtt 2.6 KB
Part 16-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.en.vtt 2.6 KB
Part 16-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.en.vtt 2.6 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.ar.vtt 2.6 KB
Part 18-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.zh-CN.vtt 2.6 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.zh-CN.vtt 2.6 KB
Part 04-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.en.vtt 2.6 KB
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.ar.vtt 2.6 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Welcome to Introduction to Python Programming-IILB-5hIeZM.ar.vtt 2.6 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.pt-BR.vtt 2.6 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/06. Ud1110 IntroPy L218 My Python Programming Setup-wrnov8J5zto.zh-CN.vtt 2.6 KB
Part 15-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.es-MX.vtt 2.59 KB
Part 08-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.en.vtt 2.59 KB
Part 11-Module 01-Lesson 01_What is Version Control/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 23 Configure Terminal-h00n9QLfbqU.ar.vtt 2.59 KB
Part 16-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.en.vtt 2.59 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.zh-CN.vtt 2.59 KB
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.ar.vtt 2.59 KB
Part 04-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.en.vtt 2.58 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/08. Types Of Errors - Part II-mbdSQ5CjdFs.zh-CN.vtt 2.58 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.pt-BR.vtt 2.58 KB
Part 15-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.en-US.vtt 2.58 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.zh-CN.vtt 2.58 KB
Part 15-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.en.vtt 2.58 KB
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.zh-CN.vtt 2.58 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.pt-BR.vtt 2.58 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.pt-BR.vtt 2.58 KB
Part 09-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.ar.vtt 2.58 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.pt-BR.vtt 2.58 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/16. ORDER BY Statement-wqj2As31LqI.ar.vtt 2.58 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.en.vtt 2.58 KB
Part 08-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.zh-CN.vtt 2.58 KB
Part 03-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.ar.vtt 2.58 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.ar.vtt 2.58 KB
Part 15-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.zh-CN.vtt 2.58 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.en.vtt 2.58 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.pt-BR.vtt 2.57 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/12. Common Types of Hypothesis Tests-8hv8KnvQ6JY.en.vtt 2.57 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 71 Merging-gQiWicrreJg.ar.vtt 2.57 KB
Part 15-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.pt-BR.vtt 2.57 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.zh-CN.vtt 2.57 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.zh-CN.vtt 2.57 KB
Part 11-Module 01-Lesson 01_What is Version Control/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 30 Configure Terminal-CCYjHfBk9hw.en.vtt 2.57 KB
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.zh-CN.vtt 2.57 KB
Part 16-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.ar.vtt 2.57 KB
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-GuBics_6HOk.pt-BR.vtt 2.57 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.pt-BR.vtt 2.57 KB
Part 12-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.ar.vtt 2.56 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/10. The Completed Program-yGDHoIOfwt8.ar.vtt 2.56 KB
Part 03-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.ar.vtt 2.56 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.zh-CN.vtt 2.56 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/02. Projects Term 1 V2-1e1y6QB34YM.ar.vtt 2.56 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.pt-BR.vtt 2.56 KB
Part 15-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.pt-BR.vtt 2.56 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.zh-CN.vtt 2.56 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.th.vtt 2.56 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.ja.vtt 2.56 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/13. LIMIT Statement-cCPHNNhBgpQ.ar.vtt 2.56 KB
Part 03-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.ar.vtt 2.56 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.pt-BR.vtt 2.56 KB
Part 16-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.ja.vtt 2.56 KB
Part 15-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.zh-CN.vtt 2.56 KB
Part 08-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.ar.vtt 2.55 KB
Part 04-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.en.vtt 2.55 KB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.en.vtt 2.55 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.ar.vtt 2.55 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.en.vtt 2.55 KB
Part 16-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.pt-BR.vtt 2.55 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/01. Adding Commits To A Repo - Intro-sLcOFQ4mGvo.ar.vtt 2.55 KB
Part 16-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.zh-CN.vtt 2.55 KB
Part 15-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.en-US.vtt 2.55 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Exploring HTML with Developer Tools-YWbCvLCBQrg.en.vtt 2.55 KB
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.en.vtt 2.55 KB
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.ar.vtt 2.55 KB
Part 15-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.en.vtt 2.54 KB
Part 18-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.en.vtt 2.54 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.ar.vtt 2.54 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.ar.vtt 2.54 KB
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Part 04-Module 01-Lesson 12_Hypothesis Testing/10. Types Of Errors - Part III-Z-srkCPsdaM.zh-CN.vtt 2.54 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.es-MX.vtt 2.54 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.pt-BR.vtt 2.54 KB
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.zh-CN.vtt 2.54 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.es-MX.vtt 2.54 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.es-MX.vtt 2.54 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.en.vtt 2.54 KB
Part 16-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.ar.vtt 2.54 KB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.pt-BR.vtt 2.54 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/18. Problem Solving Skills-el9knzvU4TM.zh-CN.vtt 2.54 KB
Part 16-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.zh-CN.vtt 2.54 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.en.vtt 2.54 KB
Part 07-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.pt-BR.vtt 2.53 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.en.vtt 2.53 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.en.vtt 2.53 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.en.vtt 2.53 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.en.vtt 2.53 KB
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-GuBics_6HOk.en.vtt 2.53 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/02. Projects Term 2-jSRJblo-Ptw.ar.vtt 2.53 KB
Part 08-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.ar.vtt 2.53 KB
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Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.pt-BR.vtt 2.53 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.en.vtt 2.53 KB
Part 16-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.zh-CN.vtt 2.53 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.en.vtt 2.52 KB
Part 15-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.en-US.vtt 2.52 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.en.vtt 2.52 KB
Part 15-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.en.vtt 2.52 KB
Part 07-Module 01-Lesson 01_What is EDA/05. Aude's Interest in Data-DDNSMG_RltY.ar.vtt 2.52 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.ar.vtt 2.52 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.en-US.vtt 2.52 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.en.vtt 2.51 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.ar.vtt 2.51 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.en.vtt 2.51 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.zh-CN.vtt 2.51 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.pt-BR.vtt 2.51 KB
Part 07-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.en.vtt 2.51 KB
Part 16-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.zh-CN.vtt 2.51 KB
Part 16-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.en.vtt 2.51 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.zh-CN.vtt 2.5 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.en-US.vtt 2.5 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/19. Order By Part II-XQCjREdOqwE.pt-BR.vtt 2.5 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/41. AND BETWEEN Operators-nBuDPneWcKY.pt-BR.vtt 2.5 KB
Part 03-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.pt-BR.vtt 2.5 KB
Part 03-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.pt-BR.vtt 2.5 KB
Part 18-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.zh-CN.vtt 2.5 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.pt-BR.vtt 2.5 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.en.vtt 2.5 KB
Part 07-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.en-US.vtt 2.5 KB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.pt-BR.vtt 2.5 KB
Part 15-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.pt-BR.vtt 2.5 KB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.pt-BR.vtt 2.5 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.ar.vtt 2.5 KB
Part 04-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.pt-BR.vtt 2.5 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/28. Arithmetic Operators-fgcJdiNECxI.ar.vtt 2.5 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.pt-BR.vtt 2.5 KB
Part 03-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.ar.vtt 2.5 KB
Part 16-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.en.vtt 2.49 KB
Part 16-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.en.vtt 2.49 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/05. Ud1110 IntroPy L212 Put A Python In Your Computer-P-Lr3WED7pg.ar.vtt 2.49 KB
Part 15-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.pt-BR.vtt 2.49 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.zh-CN.vtt 2.49 KB
Part 18-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.zh-CN.vtt 2.49 KB
Part 11-Module 01-Lesson 06_Undoing Changes/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L6 17 Soft Vs Medium Vs Hard Walkthrough-UN7ki2G2yKc.zh-CN.vtt 2.49 KB
Part 15-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.en-US.vtt 2.49 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.en.vtt 2.48 KB
Part 14-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.pt-BR.vtt 2.48 KB
Part 15-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.en.vtt 2.48 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.ar.vtt 2.48 KB
Part 03-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.ar.vtt 2.48 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/44. OR Statement-DRmkKVhe6-s.ar.vtt 2.48 KB
Part 07-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.en.vtt 2.48 KB
Part 04-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.ar.vtt 2.48 KB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.ar.vtt 2.48 KB
Part 16-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.zh-CN.vtt 2.48 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.en.vtt 2.48 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.en.vtt 2.48 KB
Part 16-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.pt-BR.vtt 2.48 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.en.vtt 2.48 KB
Part 15-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.zh-CN.vtt 2.47 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.pt-BR.vtt 2.47 KB
Part 15-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.en.vtt 2.47 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.en.vtt 2.47 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.ar.vtt 2.47 KB
Part 16-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.pt-BR.vtt 2.47 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.ja.vtt 2.47 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.zh-CN.vtt 2.47 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.zh-CN.vtt 2.47 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.pt-BR.vtt 2.46 KB
Part 15-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.en-US.vtt 2.46 KB
Part 15-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.en.vtt 2.46 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.zh-CN.vtt 2.46 KB
Part 11-Module 01-Lesson 01_What is Version Control/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 30 Configure Terminal-CCYjHfBk9hw.zh-CN.vtt 2.46 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/12. Common Types of Hypothesis Tests-8hv8KnvQ6JY.pt-BR.vtt 2.45 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.en.vtt 2.45 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.pt-BR.vtt 2.45 KB
Part 16-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.zh-CN.vtt 2.45 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.pt-BR.vtt 2.45 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 34 Finding The First Link 2-bsMtF-705EU.en.vtt 2.45 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.pt-BR.vtt 2.45 KB
Part 15-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.zh-CN.vtt 2.45 KB
Part 16-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.ar.vtt 2.45 KB
Part 07-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.en.vtt 2.45 KB
Part 18-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.en.vtt 2.45 KB
Part 09-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.pt-BR.vtt 2.44 KB
Part 11-Module 01-Lesson 06_Undoing Changes/01. Undoing Changes - Intro-Kfi7l41wUVc.ar.vtt 2.44 KB
Part 07-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.pt-BR.vtt 2.44 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.ar.vtt 2.44 KB
Part 14-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.es-MX.vtt 2.44 KB
Part 14-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.en.vtt 2.44 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/38. NOT Operator-dSQF87oW8a0.pt-BR.vtt 2.44 KB
Part 03-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.pt-BR.vtt 2.44 KB
Part 16-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.zh-CN.vtt 2.44 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.zh-CN.vtt 2.44 KB
Part 03-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.ar.vtt 2.44 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.ja.vtt 2.44 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.en.vtt 2.44 KB
Part 16-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.en.vtt 2.44 KB
Part 04-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.pt-BR.vtt 2.44 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.pt-BR.vtt 2.43 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Exploring HTML with Developer Tools-YWbCvLCBQrg.zh-CN.vtt 2.43 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.ar.vtt 2.43 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.ar.vtt 2.43 KB
Part 07-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.ja.vtt 2.43 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.en.vtt 2.43 KB
Part 04-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.zh-CN.vtt 2.43 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.en.vtt 2.43 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.zh-CN.vtt 2.42 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.ar.vtt 2.42 KB
Part 07-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.ar.vtt 2.42 KB
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.ar.vtt 2.42 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.pt-BR.vtt 2.42 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Gitfinal L1 13 Git'S Terminology-bf26adzeqMM.zh-CN.vtt 2.42 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.pt-BR.vtt 2.42 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.en.vtt 2.42 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.ar.vtt 2.42 KB
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.zh-CN.vtt 2.42 KB
Part 08-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.zh-CN.vtt 2.42 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.pt-BR.vtt 2.42 KB
Part 16-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.ja.vtt 2.42 KB
Part 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.pt-BR.vtt 2.42 KB
Part 03-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.pt-BR.vtt 2.42 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/32. LIKE Operator-O5z6eWkNip4.pt-BR.vtt 2.42 KB
Part 18-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.zh-CN.vtt 2.42 KB
Part 04-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.ar.vtt 2.42 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.pt-BR.vtt 2.42 KB
Part 07-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.ja.vtt 2.41 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.en.vtt 2.41 KB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.en.vtt 2.41 KB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.en-US.vtt 2.41 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.ar.vtt 2.41 KB
Part 03-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.pt-BR.vtt 2.41 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.zh-CN.vtt 2.41 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.en.vtt 2.41 KB
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.pt-BR.vtt 2.41 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 43 Case Study Review-jiZwuN6zTFs.zh-CN.vtt 2.41 KB
Part 03-Module 01-Lesson 02_Jupyter Notebooks/01. Jupyter-qiYDWFLyXvg.pt-BR.vtt 2.41 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.pt-BR.vtt 2.41 KB
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.ar.vtt 2.41 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.ar.vtt 2.41 KB
Part 03-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.pt-BR.vtt 2.41 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/44. OR Operator-3vLGEuXAAvA.pt-BR.vtt 2.41 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.pt-BR.vtt 2.41 KB
Part 07-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.ar.vtt 2.41 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.pt-BR.vtt 2.41 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.ar.vtt 2.4 KB
Part 08-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.ar.vtt 2.4 KB
Part 18-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.pt-BR.vtt 2.4 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.zh-CN.vtt 2.4 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.pt-BR.vtt 2.4 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.ja.vtt 2.4 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.zh-CN.vtt 2.4 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.zh-CN.vtt 2.4 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.zh-CN.vtt 2.4 KB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.en.vtt 2.4 KB
Part 12-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.pt-BR.vtt 2.4 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.en.vtt 2.4 KB
Part 16-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.ja.vtt 2.4 KB
Part 15-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.pt-BR.vtt 2.4 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.en.vtt 2.39 KB
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Part 07-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.ja.vtt 2.39 KB
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Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.zh-CN.vtt 2.37 KB
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Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.zh-CN.vtt 2.37 KB
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Part 16-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.zh-CN.vtt 2.37 KB
Part 18-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.zh-CN.vtt 2.36 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.en-US.vtt 2.36 KB
Part 04-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.ja.vtt 2.36 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.en.vtt 2.36 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.en.vtt 2.36 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 11 Git Log Output Explained-xJfurQcVYfo.ar.vtt 2.36 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.en.vtt 2.36 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.en.vtt 2.36 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.zh-CN.vtt 2.36 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.zh-CN.vtt 2.36 KB
Part 16-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.zh-CN.vtt 2.36 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.zh-CN.vtt 2.36 KB
Part 15-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.pt-BR.vtt 2.36 KB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.en.vtt 2.35 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.zh-CN.vtt 2.35 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.en-US.vtt 2.35 KB
Part 16-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.pt-BR.vtt 2.35 KB
Part 18-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.zh-CN.vtt 2.35 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-MV_e0z9kFjM.ar.vtt 2.35 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.en.vtt 2.35 KB
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Part 09-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.ar.vtt 2.35 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 34 Finding The First Link 2-bsMtF-705EU.zh-CN.vtt 2.35 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.en.vtt 2.35 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.pt-BR.vtt 2.35 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.pt-BR.vtt 2.35 KB
Part 16-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.ja.vtt 2.35 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.zh-CN.vtt 2.35 KB
Part 16-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.pt-BR.vtt 2.35 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.zh-CN.vtt 2.35 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.en.vtt 2.35 KB
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.zh-CN.vtt 2.35 KB
Part 16-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.ar.vtt 2.34 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.zh-CN.vtt 2.34 KB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.en.vtt 2.34 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.en.vtt 2.34 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.pt-BR.vtt 2.34 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.en.vtt 2.34 KB
Part 08-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.ar.vtt 2.34 KB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.en.vtt 2.34 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.zh-CN.vtt 2.34 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.zh-CN.vtt 2.34 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.zh-CN.vtt 2.34 KB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.pt-BR.vtt 2.33 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.ar.vtt 2.33 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.pt-BR.vtt 2.33 KB
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.pt-BR.vtt 2.33 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.pt-BR.vtt 2.33 KB
Part 15-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.pt-BR.vtt 2.33 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/22. L2 07 Lists And Membership Operators II V3-3Nj-b-ZzqH8.pt-BR.vtt 2.33 KB
Part 16-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.pt-BR.vtt 2.33 KB
Part 16-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.en.vtt 2.32 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.en.vtt 2.32 KB
Part 18-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.zh-CN.vtt 2.32 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.pt-BR.vtt 2.32 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.pt-BR.vtt 2.32 KB
Part 03-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.en.vtt 2.32 KB
Part 14-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.en.vtt 2.32 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.pt-BR.vtt 2.32 KB
Part 07-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.en.vtt 2.31 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.en.vtt 2.31 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.en.vtt 2.31 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.en.vtt 2.31 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.ja.vtt 2.31 KB
Part 16-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.zh-CN.vtt 2.31 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.zh-CN.vtt 2.31 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.pt-BR.vtt 2.31 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.ar.vtt 2.31 KB
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.ar.vtt 2.31 KB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.pt-BR.vtt 2.31 KB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.ar.vtt 2.3 KB
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.ar.vtt 2.3 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.en.vtt 2.3 KB
Part 15-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.en-US.vtt 2.3 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.en.vtt 2.3 KB
Part 09-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.ar.vtt 2.3 KB
Part 04-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.ar.vtt 2.3 KB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.ar.vtt 2.3 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.zh-CN.vtt 2.3 KB
Part 15-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.en.vtt 2.3 KB
Part 15-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.zh-CN.vtt 2.3 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/13. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.zh-CN.vtt 2.3 KB
Part 15-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.en-US.vtt 2.3 KB
Part 07-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.ja.vtt 2.29 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.en.vtt 2.29 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.ja.vtt 2.29 KB
Part 15-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.en.vtt 2.29 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.ja.vtt 2.29 KB
Part 16-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.zh-CN.vtt 2.29 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.zh-CN.vtt 2.29 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.en.vtt 2.29 KB
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.pt-BR.vtt 2.29 KB
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.en.vtt 2.29 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/41. AND BETWEEN Operators-nBuDPneWcKY.en.vtt 2.28 KB
Part 03-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.en.vtt 2.28 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.en.vtt 2.28 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.pt-BR.vtt 2.28 KB
Part 15-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.pt-BR.vtt 2.28 KB
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.en.vtt 2.28 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/04. Setting Up Hypotheses - Part II-nByvHz77GiA.zh-CN.vtt 2.28 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.ar.vtt 2.28 KB
Part 16-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.ar.vtt 2.28 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.pt-BR.vtt 2.28 KB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.pt-BR.vtt 2.28 KB
Part 14-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.zh-CN.vtt 2.28 KB
Part 12-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.ar.vtt 2.28 KB
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.ar.vtt 2.28 KB
Part 11-Module 01-Lesson 01_What is Version Control/01. Gitfinal L1 03 Version Control Systems-b7TjsVoTo3Q.pt-BR.vtt 2.28 KB
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.pt-BR.vtt 2.27 KB
Part 15-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.en-US.vtt 2.27 KB
Part 16-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.en.vtt 2.27 KB
Part 16-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.pt-BR.vtt 2.27 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.pt-BR.vtt 2.27 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.en.vtt 2.27 KB
Part 15-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.en.vtt 2.27 KB
Part 16-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.zh-CN.vtt 2.27 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/08. Self JOINs-tw_VzEGBOvI.en.vtt 2.27 KB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.en.vtt 2.27 KB
Part 07-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.ar.vtt 2.27 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/02. Projects Term 1 V2-1e1y6QB34YM.pt-BR.vtt 2.27 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.ar.vtt 2.27 KB
Part 14-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.pt-BR.vtt 2.27 KB
Part 16-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.en.vtt 2.27 KB
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-GuBics_6HOk.zh-CN.vtt 2.27 KB
Part 04-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.pt-BR.vtt 2.27 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.ar.vtt 2.27 KB
Part 16-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.ja.vtt 2.27 KB
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.ar.vtt 2.27 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function-XUZIGbX3JIg.ar.vtt 2.26 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.pt-BR.vtt 2.26 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.pt-BR.vtt 2.26 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 34 Finding The First Link 2-bsMtF-705EU.pt-BR.vtt 2.26 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.en.vtt 2.26 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Continue Crawl Solution-cFwJ_MO3ofs.en.vtt 2.26 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.zh-CN.vtt 2.26 KB
Part 16-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.ar.vtt 2.26 KB
Part 07-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.pt-BR.vtt 2.26 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.en.vtt 2.26 KB
Part 15-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.zh-CN.vtt 2.26 KB
Part 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.en.vtt 2.26 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.ar.vtt 2.26 KB
Part 16-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.zh-CN.vtt 2.25 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.en.vtt 2.25 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.en.vtt 2.25 KB
Part 07-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.ar.vtt 2.25 KB
Part 16-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.ar.vtt 2.25 KB
Part 04-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.zh-CN.vtt 2.25 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/22. WHERE Statements -mN0uTnlXaxg.en.vtt 2.25 KB
Part 03-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.en.vtt 2.25 KB
Part 04-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.zh-CN.vtt 2.25 KB
Part 07-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.pt-BR.vtt 2.25 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.ja.vtt 2.25 KB
Part 16-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.pt-BR.vtt 2.25 KB
Part 16-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.en.vtt 2.25 KB
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.pt-BR.vtt 2.25 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/08. Self JOINs-tw_VzEGBOvI.pt-BR.vtt 2.24 KB
Part 14-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.es-MX.vtt 2.24 KB
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.zh-CN.vtt 2.24 KB
Part 15-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.pt-BR.vtt 2.24 KB
Part 15-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.zh-CN.vtt 2.24 KB
Part 18-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.ar.vtt 2.24 KB
Part 08-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.ar.vtt 2.24 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.ar.vtt 2.24 KB
Part 07-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.zh-CN.vtt 2.23 KB
Part 15-Module 02-Lesson 05_Trees/13. BST Complications-pcB0wV7myy4.zh-CN.vtt 2.23 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.ar.vtt 2.23 KB
Part 16-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.en.vtt 2.23 KB
Part 08-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.ar.vtt 2.23 KB
Part 15-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.en.vtt 2.23 KB
Part 16-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.ar.vtt 2.23 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.en.vtt 2.23 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.ar.vtt 2.23 KB
Part 15-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.en-US.vtt 2.23 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.pt-BR.vtt 2.23 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.pt-BR.vtt 2.23 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.zh-CN.vtt 2.23 KB
Part 09-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.en.vtt 2.23 KB
Part 16-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.pt-BR.vtt 2.23 KB
Part 18-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.en.vtt 2.23 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.zh-CN.vtt 2.23 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 1-APRpwqFpGwI.ar.vtt 2.23 KB
Part 03-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.en.vtt 2.22 KB
Part 04-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.zh-CN.vtt 2.22 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.en.vtt 2.22 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.zh-CN.vtt 2.22 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/38. NOT Operator-dSQF87oW8a0.en.vtt 2.22 KB
Part 15-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.zh-CN.vtt 2.22 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.en-US.vtt 2.22 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.zh-CN.vtt 2.22 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.pt-BR.vtt 2.22 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.en.vtt 2.22 KB
Part 08-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.en.vtt 2.22 KB
Part 14-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.zh-CN.vtt 2.22 KB
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.en.vtt 2.22 KB
Part 11-Module 01-Lesson 01_What is Version Control/01. Gitfinal L1 03 Version Control Systems-b7TjsVoTo3Q.en.vtt 2.22 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.en.vtt 2.22 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.pt-BR.vtt 2.22 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.zh-CN.vtt 2.22 KB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.pt-BR.vtt 2.22 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.ar.vtt 2.22 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/25. Multiple Testing Corrections-DuMgeHrkIF0.en.vtt 2.21 KB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.ja.vtt 2.21 KB
Part 08-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.ar.vtt 2.21 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/25. Multiple Testing Corrections-DuMgeHrkIF0.pt-BR.vtt 2.21 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.pt-BR.vtt 2.21 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.zh-CN.vtt 2.21 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.ar.vtt 2.21 KB
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.ar.vtt 2.21 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.ar.vtt 2.21 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.zh-CN.vtt 2.21 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.ar.vtt 2.21 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.ar.vtt 2.2 KB
Part 16-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.en.vtt 2.2 KB
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.zh-CN.vtt 2.2 KB
Part 07-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.zh-CN.vtt 2.2 KB
Part 15-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.zh-CN.vtt 2.2 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.pt-BR.vtt 2.2 KB
Part 07-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.zh-CN.vtt 2.2 KB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.th.vtt 2.2 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.zh-CN.vtt 2.2 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/01. Welcome To DAND Term 2-OOcC8OUJmc0.ar.vtt 2.2 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/20. Connecting Errors and P-Values-hFNjd5l9CLs.en.vtt 2.2 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.ar.vtt 2.19 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.en.vtt 2.19 KB
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.ar.vtt 2.19 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.zh-CN.vtt 2.19 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.pt-BR.vtt 2.19 KB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.ja.vtt 2.19 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.ja.vtt 2.19 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.pt-BR.vtt 2.19 KB
Part 16-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.ar.vtt 2.19 KB
Part 04-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.ar.vtt 2.19 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 18 Recap-xqD9ImXXXHk.ar.vtt 2.19 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.ar.vtt 2.19 KB
Part 16-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.en.vtt 2.19 KB
Part 09-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.pt-BR.vtt 2.19 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.en.vtt 2.19 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.ar.vtt 2.19 KB
Part 15-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.zh-CN.vtt 2.19 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.ar.vtt 2.19 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.ar.vtt 2.19 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.zh-CN.vtt 2.19 KB
Part 16-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.pt-BR.vtt 2.19 KB
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.pt-BR.vtt 2.19 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.zh-CN.vtt 2.18 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/12. Common Types of Hypothesis Tests-8hv8KnvQ6JY.zh-CN.vtt 2.18 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Continue Crawl Solution-cFwJ_MO3ofs.pt-BR.vtt 2.18 KB
Part 07-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.pt-BR.vtt 2.18 KB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.en.vtt 2.18 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.zh-CN.vtt 2.18 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/02. What's Ahead-ggbCydfI1JM.pt-BR.vtt 2.18 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-3kH4ei9l4h8.ar.vtt 2.18 KB
Part 18-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.en.vtt 2.18 KB
Part 07-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.en.vtt 2.18 KB
Part 18-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.zh-CN.vtt 2.18 KB
Part 11-Module 01-Lesson 01_What is Version Control/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 11 Google Docs Revision History Walkthrough-GcvvbdKEchk.ar.vtt 2.17 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.pt-BR.vtt 2.17 KB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.en.vtt 2.17 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.en.vtt 2.17 KB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.en.vtt 2.17 KB
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.en.vtt 2.17 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Businesses Choose Databases-j4ey7--h9r8.en.vtt 2.17 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.en.vtt 2.17 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.en.vtt 2.17 KB
Part 07-Module 01-Lesson 01_What is EDA/10. Course Overview-W8N0aSMPff8.ar.vtt 2.17 KB
Part 15-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.zh-CN.vtt 2.17 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 03 Tagging Overview-D4VdXT72ASE.ar.vtt 2.17 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.es-ES.vtt 2.17 KB
Part 04-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.pt-BR.vtt 2.17 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.pt-BR.vtt 2.17 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.pt-BR.vtt 2.17 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.pt-BR.vtt 2.17 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.pt-BR.vtt 2.17 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.zh-CN.vtt 2.17 KB
Part 12-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.ar.vtt 2.16 KB
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.pt-BR.vtt 2.16 KB
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.ar.vtt 2.16 KB
Part 12-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.en.vtt 2.16 KB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.ja.vtt 2.16 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.ar.vtt 2.16 KB
Part 04-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.ar.vtt 2.16 KB
Part 16-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.zh-CN.vtt 2.16 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.en.vtt 2.16 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.ar.vtt 2.15 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.ar.vtt 2.15 KB
Part 16-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.ja.vtt 2.15 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.zh-CN.vtt 2.15 KB
Part 15-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.pt-BR.vtt 2.15 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 27 Confession Corner-xtsugblSwrU.ar.vtt 2.15 KB
Part 07-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.ar.vtt 2.14 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/08. Ud1110 IntroPy L3 37 Reading Existing Code-0Pg3HryU9Z4.ar.vtt 2.14 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.ar.vtt 2.14 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/44. OR Operator-3vLGEuXAAvA.en.vtt 2.14 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.zh-CN.vtt 2.14 KB
Part 03-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.en.vtt 2.14 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.en.vtt 2.14 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.zh-CN.vtt 2.14 KB
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.en.vtt 2.14 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.zh-CN.vtt 2.14 KB
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.ja.vtt 2.14 KB
Part 04-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.zh-CN.vtt 2.14 KB
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.ar.vtt 2.14 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.pt-BR.vtt 2.14 KB
Part 16-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.ar.vtt 2.14 KB
Part 18-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.pt-BR.vtt 2.14 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.zh-CN.vtt 2.14 KB
Part 16-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.pt-BR.vtt 2.13 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/12. Ud1110 IntroPy L237 Break Up Your Code Ideas-qrp8r48BPUs.ar.vtt 2.13 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.zh-CN.vtt 2.13 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.ja.vtt 2.13 KB
Part 18-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.zh-CN.vtt 2.13 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.zh-CN.vtt 2.13 KB
Part 16-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.pt-BR.vtt 2.13 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.zh-CN.vtt 2.13 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/06. Types Of Errors - Part I-aw6GMxIvENc.en.vtt 2.13 KB
Part 09-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.en.vtt 2.13 KB
Part 09-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.zh-CN.vtt 2.13 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.ja.vtt 2.13 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.pt-BR.vtt 2.13 KB
Part 15-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.pt-BR.vtt 2.13 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.en.vtt 2.13 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.ja.vtt 2.13 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.zh-CN.vtt 2.13 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.es-ES.vtt 2.13 KB
Part 08-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.ar.vtt 2.13 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.zh-CN.vtt 2.12 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.zh-CN.vtt 2.12 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.zh-CN.vtt 2.12 KB
Part 04-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.pt-BR.vtt 2.12 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.en.vtt 2.12 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.zh-CN.vtt 2.12 KB
Part 18-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.pt-BR.vtt 2.12 KB
Part 07-Module 01-Lesson 01_What is EDA/03. Go Exploring-dias-YUpewk.ja.vtt 2.12 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.zh-CN.vtt 2.12 KB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.ar.vtt 2.12 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.en.vtt 2.11 KB
Part 15-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.pt-BR.vtt 2.11 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.zh-CN.vtt 2.11 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.it.vtt 2.11 KB
Part 04-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.zh-CN.vtt 2.11 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.en.vtt 2.11 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.en-US.vtt 2.11 KB
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.ja.vtt 2.11 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.ar.vtt 2.11 KB
Part 03-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.pt-BR.vtt 2.11 KB
Part 03-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.pt-BR.vtt 2.11 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/13. LIMIT Statement-cCPHNNhBgpQ.pt-BR.vtt 2.11 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.zh-CN.vtt 2.11 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/16. ORDER BY Statement-wqj2As31LqI.pt-BR.vtt 2.11 KB
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.ar.vtt 2.11 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.en.vtt 2.11 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.pt-BR.vtt 2.11 KB
Part 15-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.zh-CN.vtt 2.1 KB
Part 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.zh-CN.vtt 2.1 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.es-ES.vtt 2.1 KB
Part 04-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.pt-BR.vtt 2.1 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.es-MX.vtt 2.1 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.es-MX.vtt 2.1 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.es-MX.vtt 2.1 KB
Part 07-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.en.vtt 2.1 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.pt-BR.vtt 2.1 KB
Part 08-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.pt-BR.vtt 2.1 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.zh-CN.vtt 2.1 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.zh-CN.vtt 2.1 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.zh-CN.vtt 2.1 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.en.vtt 2.1 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/01. Welcome!-KJT4Z0xpHns.pt-BR.vtt 2.1 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.zh-CN.vtt 2.1 KB
Part 04-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.it.vtt 2.09 KB
Part 16-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.ar.vtt 2.09 KB
Part 09-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.ar.vtt 2.09 KB
Part 16-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.ar.vtt 2.09 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.pt-BR.vtt 2.09 KB
Part 08-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.zh-CN.vtt 2.09 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.en.vtt 2.09 KB
Part 07-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.pt-BR.vtt 2.09 KB
Part 16-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.en.vtt 2.09 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/28. Arithmetic Operators-fgcJdiNECxI.pt-BR.vtt 2.09 KB
Part 16-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.zh-CN.vtt 2.09 KB
Part 03-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.pt-BR.vtt 2.09 KB
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.en.vtt 2.09 KB
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.en.vtt 2.08 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.ar.vtt 2.08 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.pt-BR.vtt 2.08 KB
Part 11-Module 01-Lesson 01_What is Version Control/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 23 Configure Terminal-h00n9QLfbqU.pt-BR.vtt 2.08 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/08. Self JOINs-tw_VzEGBOvI.zh-CN.vtt 2.08 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.zh-CN.vtt 2.08 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.ar.vtt 2.08 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.pt-BR.vtt 2.08 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.zh-CN.vtt 2.08 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.zh-CN.vtt 2.08 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.zh-CN.vtt 2.08 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.pt-BR.vtt 2.08 KB
Part 08-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.ar.vtt 2.08 KB
Part 15-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.es-MX.vtt 2.08 KB
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.ar.vtt 2.08 KB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.ja.vtt 2.08 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/19. Order By Part II-XQCjREdOqwE.en.vtt 2.08 KB
Part 03-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.en.vtt 2.08 KB
Part 16-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.pt-BR.vtt 2.08 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.ar.vtt 2.08 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.pt-BR.vtt 2.07 KB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.ar.vtt 2.07 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.en.vtt 2.07 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/02. Projects Term 2-jSRJblo-Ptw.pt-BR.vtt 2.07 KB
Part 15-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.zh-CN.vtt 2.07 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.en.vtt 2.07 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Continue Crawl Solution-cFwJ_MO3ofs.zh-CN.vtt 2.07 KB
Part 12-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.zh-CN.vtt 2.07 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.zh-CN.vtt 2.07 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.pt-BR.vtt 2.07 KB
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.ja.vtt 2.07 KB
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.ar.vtt 2.07 KB
Part 07-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.en-US.vtt 2.07 KB
Part 08-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.pt-BR.vtt 2.07 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/01. Welcome!-KJT4Z0xpHns.en.vtt 2.07 KB
Part 08-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.ar.vtt 2.07 KB
Part 12-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.pt-BR.vtt 2.07 KB
Part 03-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.ar.vtt 2.07 KB
Part 16-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.en.vtt 2.07 KB
Part 07-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.en.vtt 2.07 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/02. Introduction-Z8WNfx9Oq9s.ar.vtt 2.07 KB
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.ar.vtt 2.07 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.zh-CN.vtt 2.07 KB
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.en.vtt 2.06 KB
Part 15-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.zh-CN.vtt 2.06 KB
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.ar.vtt 2.06 KB
Part 04-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.en.vtt 2.06 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.zh-CN.vtt 2.06 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.en.vtt 2.06 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.zh-CN.vtt 2.06 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.zh-CN.vtt 2.06 KB
Part 15-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.en-US.vtt 2.06 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.zh-CN.vtt 2.06 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/05. Why Businesses Choose Databases-j4ey7--h9r8.zh-CN.vtt 2.06 KB
Part 03-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.zh-CN.vtt 2.06 KB
Part 12-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.pt-BR.vtt 2.06 KB
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.ja.vtt 2.06 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.zh-CN.vtt 2.06 KB
Part 03-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.en.vtt 2.06 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.zh-CN.vtt 2.06 KB
Part 15-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.en.vtt 2.06 KB
Part 18-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.en.vtt 2.05 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.en.vtt 2.05 KB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.ar.vtt 2.05 KB
Part 15-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.zh-CN.vtt 2.05 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.ar.vtt 2.05 KB
Part 07-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.ar.vtt 2.05 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/22. WHERE Statements -mN0uTnlXaxg.zh-CN.vtt 2.05 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.en.vtt 2.05 KB
Part 03-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.zh-CN.vtt 2.05 KB
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.th.vtt 2.05 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.en.vtt 2.05 KB
Part 08-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.pt-BR.vtt 2.05 KB
Part 15-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.pt-BR.vtt 2.04 KB
Part 16-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.ar.vtt 2.04 KB
Part 16-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.ar.vtt 2.04 KB
Part 08-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.pt-BR.vtt 2.04 KB
Part 16-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.ar.vtt 2.04 KB
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.en.vtt 2.04 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.zh-CN.vtt 2.04 KB
Part 07-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.zh-CN.vtt 2.04 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.ar.vtt 2.04 KB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.en.vtt 2.04 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.ja.vtt 2.04 KB
Part 07-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.ja.vtt 2.04 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.ar.vtt 2.04 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.ar.vtt 2.04 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/41. AND BETWEEN Operators-nBuDPneWcKY.zh-CN.vtt 2.04 KB
Part 03-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.zh-CN.vtt 2.04 KB
Part 07-Module 01-Lesson 01_What is EDA/08. Our Approach for This Course-dBsf-szQ00s.ar.vtt 2.04 KB
Part 07-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.pt-BR.vtt 2.04 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.en.vtt 2.04 KB
Part 09-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.zh-CN.vtt 2.03 KB
Part 07-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.en.vtt 2.03 KB
Part 15-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.en.vtt 2.03 KB
Part 16-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.pt-BR.vtt 2.03 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.ar.vtt 2.03 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/10. Time Commitment-d-VfUw7wNEQ.pt-BR.vtt 2.03 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/11. Time Commitment-d-VfUw7wNEQ.pt-BR.vtt 2.03 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.ar.vtt 2.03 KB
Part 03-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.zh-CN.vtt 2.03 KB
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.ja.vtt 2.03 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.zh-CN.vtt 2.03 KB
Part 18-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.en.vtt 2.03 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.ja.vtt 2.03 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.ar.vtt 2.03 KB
Part 16-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.en.vtt 2.03 KB
Part 04-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.en.vtt 2.02 KB
Part 04-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.en.vtt 2.02 KB
Part 16-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.zh-CN.vtt 2.02 KB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.en.vtt 2.02 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.en.vtt 2.02 KB
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.ja.vtt 2.02 KB
Part 16-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.pt-BR.vtt 2.02 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.en.vtt 2.02 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/07. Ud1110 IntroPy L5 30 Finding The First Link-Z-uuXDrMzqM.ar.vtt 2.02 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.pt-BR.vtt 2.02 KB
Part 07-Module 01-Lesson 01_What is EDA/03. Go Exploring-dias-YUpewk.en.vtt 2.02 KB
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.pt-BR.vtt 2.02 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.zh-CN.vtt 2.02 KB
Part 16-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.pt-BR.vtt 2.02 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.pt-BR.vtt 2.02 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.en.vtt 2.02 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.ja.vtt 2.01 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/02. What's Ahead-ggbCydfI1JM.en.vtt 2.01 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.pt-BR.vtt 2.01 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.ja.vtt 2.01 KB
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.ar.vtt 2.01 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.zh-CN.vtt 2.01 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.es-ES.vtt 2.01 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.pt-BR.vtt 2.01 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.pt-BR.vtt 2.01 KB
Part 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.zh-CN.vtt 2.01 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.zh-CN.vtt 2.01 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.pt-BR.vtt 2.01 KB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.zh-CN.vtt 2.01 KB
Part 16-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.en.vtt 2.01 KB
Part 16-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.zh-CN.vtt 2.01 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.ar.vtt 2.01 KB
Part 15-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.pt-BR.vtt 2.01 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/38. NOT Operator-dSQF87oW8a0.zh-CN.vtt 2.01 KB
Part 03-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.zh-CN.vtt 2.01 KB
Part 07-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.ja.vtt 2.01 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.ar.vtt 2.01 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/10. Time Commitment-d-VfUw7wNEQ.en-US.vtt 2 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/11. Time Commitment-d-VfUw7wNEQ.en-US.vtt 2 KB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.pt-BR.vtt 2 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.pt-BR.vtt 2 KB
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.pt-BR.vtt 2 KB
Part 16-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.zh-CN.vtt 2 KB
Part 16-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.en.vtt 2 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/11. Time Commitment-d-VfUw7wNEQ.en.vtt 2 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/10. Time Commitment-d-VfUw7wNEQ.en.vtt 2 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.en.vtt 2 KB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.zh-CN.vtt 2 KB
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.th.vtt 2 KB
Part 08-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.pt-BR.vtt 2 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.ar.vtt 2 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.pt-BR.vtt 2 KB
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.ar.vtt 2 KB
Part 16-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.en.vtt 2 KB
Part 04-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.ar.vtt 2 KB
Part 15-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.pt-BR.vtt 2 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/01. Adding Commits To A Repo - Intro-sLcOFQ4mGvo.en.vtt 2 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Welcome to Introduction to Python Programming-IILB-5hIeZM.en.vtt 2 KB
Part 16-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.zh-CN.vtt 2 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.en.vtt 1.99 KB
Part 15-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.zh-CN.vtt 1.99 KB
Part 16-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.en.vtt 1.99 KB
Part 04-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.it.vtt 1.99 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/01. Welcome!-KJT4Z0xpHns.ja.vtt 1.99 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.pt-BR.vtt 1.99 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.ar.vtt 1.99 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.es-MX.vtt 1.99 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/10. The Completed Program-yGDHoIOfwt8.en.vtt 1.99 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.en-US.vtt 1.99 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.zh-CN.vtt 1.99 KB
Part 15-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.en-US.vtt 1.99 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.zh-CN.vtt 1.99 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/21. Conclusions In Hypothesis Testing-I0Mo7hcxahY.pt-BR.vtt 1.99 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/06. Types Of Errors - Part I-aw6GMxIvENc.pt-BR.vtt 1.99 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.en.vtt 1.99 KB
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.pt-BR.vtt 1.99 KB
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.pt-BR.vtt 1.99 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.en.vtt 1.99 KB
Part 15-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.en.vtt 1.99 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.en.vtt 1.99 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.zh-CN.vtt 1.98 KB
Part 16-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.en-US.vtt 1.98 KB
Part 07-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.ar.vtt 1.98 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.zh-CN.vtt 1.98 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.pt-BR.vtt 1.98 KB
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.pt-BR.vtt 1.98 KB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.pt-BR.vtt 1.98 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.pt-BR.vtt 1.98 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.pt-BR.vtt 1.98 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.pt-BR.vtt 1.98 KB
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.ar.vtt 1.98 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.zh-CN.vtt 1.98 KB
Part 15-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.pt-BR.vtt 1.98 KB
Part 04-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.ja.vtt 1.98 KB
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.en.vtt 1.98 KB
Part 04-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.es-ES.vtt 1.98 KB
Part 11-Module 01-Lesson 01_What is Version Control/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 23 Configure Terminal-h00n9QLfbqU.en.vtt 1.97 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.ar.vtt 1.97 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.ar.vtt 1.97 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/21. Conclusions In Hypothesis Testing-I0Mo7hcxahY.en.vtt 1.97 KB
Part 15-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.zh-CN.vtt 1.97 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/05. Ud1110 IntroPy L212 Put A Python In Your Computer-P-Lr3WED7pg.zh-CN.vtt 1.97 KB
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.ar.vtt 1.97 KB
Part 16-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.zh-CN.vtt 1.97 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.pt-BR.vtt 1.97 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.zh-CN.vtt 1.97 KB
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.pt-BR.vtt 1.97 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.zh-CN.vtt 1.97 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.pt-BR.vtt 1.97 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.ar.vtt 1.97 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/07. Types Of Statements-vLvJbIz94C4.ar.vtt 1.97 KB
Part 03-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.ar.vtt 1.97 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/20. Connecting Errors and P-Values-hFNjd5l9CLs.pt-BR.vtt 1.97 KB
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.ar.vtt 1.97 KB
Part 16-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.zh-CN.vtt 1.97 KB
Part 04-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.pt-BR.vtt 1.96 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.pt-BR.vtt 1.96 KB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.ar.vtt 1.96 KB
Part 16-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.pt-BR.vtt 1.96 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.zh-CN.vtt 1.96 KB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.en.vtt 1.96 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function-XUZIGbX3JIg.ja.vtt 1.96 KB
Part 16-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.zh-CN.vtt 1.96 KB
Part 16-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.zh-CN.vtt 1.96 KB
Part 07-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.en.vtt 1.95 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/32. LIKE Operator-O5z6eWkNip4.en.vtt 1.95 KB
Part 03-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.en.vtt 1.95 KB
Part 07-Module 01-Lesson 01_What is EDA/03. Go Exploring-dias-YUpewk.pt-BR.vtt 1.95 KB
Part 16-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.pt-BR.vtt 1.95 KB
Part 04-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.es-ES.vtt 1.95 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.es-MX.vtt 1.95 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.es-MX.vtt 1.95 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.es-MX.vtt 1.95 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.ar.vtt 1.95 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.en.vtt 1.95 KB
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.zh-CN.vtt 1.95 KB
Part 07-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.pt-BR.vtt 1.95 KB
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.pt-BR.vtt 1.95 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.ar.vtt 1.94 KB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.ar.vtt 1.94 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.zh-CN.vtt 1.94 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.th.vtt 1.94 KB
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.zh-CN.vtt 1.94 KB
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.en.vtt 1.94 KB
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.en.vtt 1.94 KB
Part 12-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.ar.vtt 1.94 KB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.zh-CN.vtt 1.94 KB
Part 18-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.zh-CN.vtt 1.94 KB
Part 16-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.zh-CN.vtt 1.94 KB
Part 16-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.ja.vtt 1.94 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/02. Projects Term 2-jSRJblo-Ptw.en.vtt 1.94 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.ja.vtt 1.94 KB
Part 08-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.en.vtt 1.94 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.pt-BR.vtt 1.94 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.en.vtt 1.94 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.pt-BR.vtt 1.94 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.pt-BR.vtt 1.93 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/16. ORDER BY Statement-wqj2As31LqI.en.vtt 1.93 KB
Part 03-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.en.vtt 1.93 KB
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.en-GB.vtt 1.93 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.ar.vtt 1.93 KB
Part 16-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.en.vtt 1.93 KB
Part 07-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.ja.vtt 1.93 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.ar.vtt 1.93 KB
Part 15-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.zh-CN.vtt 1.93 KB
Part 18-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.zh-CN.vtt 1.93 KB
Part 09-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.zh-CN.vtt 1.93 KB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.zh-CN.vtt 1.93 KB
Part 16-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.ar.vtt 1.93 KB
Part 07-Module 01-Lesson 01_What is EDA/05. Aude's Interest in Data-DDNSMG_RltY.en.vtt 1.93 KB
Part 12-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.en.vtt 1.92 KB
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.ar.vtt 1.92 KB
Part 04-Module 01-Lesson 16_Logistic Regression/01. Introduction to Logistic Regression-P_f2RjjnPEg.pt-BR.vtt 1.92 KB
Part 04-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.en.vtt 1.92 KB
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.zh-CN.vtt 1.92 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.ar.vtt 1.92 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/35. IN Operator-_JPO7wwX3uA.ar.vtt 1.92 KB
Part 03-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.ar.vtt 1.92 KB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.zh-CN.vtt 1.92 KB
Part 08-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.en.vtt 1.92 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.zh-CN.vtt 1.92 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.ar.vtt 1.92 KB
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.zh-CN.vtt 1.92 KB
Part 07-Module 01-Lesson 01_What is EDA/05. Aude's Interest in Data-DDNSMG_RltY.pt-BR.vtt 1.92 KB
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.en.vtt 1.92 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.en.vtt 1.92 KB
Part 08-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.zh-CN.vtt 1.92 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.ar.vtt 1.92 KB
Part 12-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.zh-CN.vtt 1.92 KB
Part 16-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.pt-BR.vtt 1.92 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.pt-BR.vtt 1.92 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.en.vtt 1.92 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.ar.vtt 1.91 KB
Part 11-Module 01-Lesson 02_Create A Git Repo/01. Creating New Repositories - Intro-KT163BkqIeg.pt-BR.vtt 1.91 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.en.vtt 1.91 KB
Part 15-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.en-US.vtt 1.91 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.zh-CN.vtt 1.91 KB
Part 16-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.ar.vtt 1.91 KB
Part 07-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.zh-CN.vtt 1.91 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. What are we going to do-rK6YlbBiKQM.en.vtt 1.91 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.en.vtt 1.91 KB
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.en.vtt 1.91 KB
Part 15-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.en.vtt 1.91 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/05. Ud1110 IntroPy L212 Put A Python In Your Computer-P-Lr3WED7pg.en.vtt 1.91 KB
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.pt-BR.vtt 1.91 KB
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.en.vtt 1.91 KB
Part 11-Module 01-Lesson 01_What is Version Control/01. Gitfinal L1 03 Version Control Systems-b7TjsVoTo3Q.zh-CN.vtt 1.91 KB
Part 16-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.ar.vtt 1.91 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.ja.vtt 1.91 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.ar.vtt 1.91 KB
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.ar.vtt 1.91 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.ar.vtt 1.9 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/10. The Completed Program-yGDHoIOfwt8.pt-BR.vtt 1.9 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.pt-BR.vtt 1.9 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.zh-CN.vtt 1.9 KB
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.zh-CN.vtt 1.9 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.pt-BR.vtt 1.9 KB
Part 04-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.en.vtt 1.9 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.zh-CN.vtt 1.9 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.pt-BR.vtt 1.9 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/25. Multiple Testing Corrections-DuMgeHrkIF0.zh-CN.vtt 1.9 KB
Part 04-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.pt-BR.vtt 1.9 KB
Part 16-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.zh-CN.vtt 1.9 KB
Part 07-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.ja.vtt 1.9 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.es-MX.vtt 1.9 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.ar.vtt 1.9 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.en.vtt 1.9 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/02. Projects Term 1 V2-1e1y6QB34YM.en.vtt 1.9 KB
Part 16-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.en.vtt 1.9 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.zh-CN.vtt 1.9 KB
Part 03-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.en.vtt 1.9 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.pt-BR.vtt 1.9 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.zh-CN.vtt 1.89 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.pt-BR.vtt 1.89 KB
Part 16-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.en.vtt 1.89 KB
Part 16-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.ar.vtt 1.89 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.pt-BR.vtt 1.89 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function-XUZIGbX3JIg.pt-BR.vtt 1.89 KB
Part 09-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.en.vtt 1.89 KB
Part 12-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.en.vtt 1.89 KB
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.ja.vtt 1.89 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.ja.vtt 1.89 KB
Part 04-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.zh-CN.vtt 1.89 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.ar.vtt 1.89 KB
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Part 08-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.pt-BR.vtt 1.89 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/05. Ud1110 IntroPy L212 Put A Python In Your Computer-P-Lr3WED7pg.pt-BR.vtt 1.89 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Welcome to Introduction to Python Programming-IILB-5hIeZM.zh-CN.vtt 1.89 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.en.vtt 1.89 KB
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.ar.vtt 1.89 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/28. Arithmetic Operators-fgcJdiNECxI.en.vtt 1.89 KB
Part 15-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.zh-CN.vtt 1.89 KB
Part 03-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.en.vtt 1.89 KB
Part 04-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.ar.vtt 1.88 KB
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.ja.vtt 1.88 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.ja.vtt 1.88 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.pt-BR.vtt 1.88 KB
Part 07-Module 01-Lesson 01_What is EDA/02. Data is Ubiquitous-ieiQqLicBjg.ar.vtt 1.88 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.ar.vtt 1.88 KB
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.ar.vtt 1.88 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.ar.vtt 1.88 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.pt-BR.vtt 1.88 KB
Part 09-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.pt-BR.vtt 1.88 KB
Part 16-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.pt-BR.vtt 1.88 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.pt-BR.vtt 1.88 KB
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.ar.vtt 1.88 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.pt-BR.vtt 1.88 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-MV_e0z9kFjM.pt-BR.vtt 1.88 KB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.ar.vtt 1.88 KB
Part 04-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.pt-BR.vtt 1.88 KB
Part 15-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.pt-BR.vtt 1.88 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.ar.vtt 1.88 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.ja.vtt 1.88 KB
Part 04-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.en.vtt 1.88 KB
Part 15-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.pt-BR.vtt 1.87 KB
Part 12-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.zh-CN.vtt 1.87 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.ar.vtt 1.87 KB
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.zh-CN.vtt 1.87 KB
Part 09-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.pt-BR.vtt 1.87 KB
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.zh-CN.vtt 1.87 KB
Part 16-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.ar.vtt 1.87 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-MV_e0z9kFjM.ja.vtt 1.87 KB
Part 03-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.zh-CN.vtt 1.87 KB
Part 11-Module 01-Lesson 01_What is Version Control/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 23 Configure Terminal-h00n9QLfbqU.zh-CN.vtt 1.87 KB
Part 03-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.ar.vtt 1.87 KB
Part 09-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.ar.vtt 1.87 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.en.vtt 1.87 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.en.vtt 1.87 KB
Part 16-Module 01-Lesson 07_Regressions/37. Regression Mini-Project Video-CrD9jN3rBM8.ar.vtt 1.87 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Welcome to Introduction to Python Programming-IILB-5hIeZM.pt-BR.vtt 1.87 KB
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.pt-BR.vtt 1.87 KB
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.it.vtt 1.87 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/26. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.pt-BR.vtt 1.87 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/44. OR Operator-3vLGEuXAAvA.zh-CN.vtt 1.87 KB
Part 03-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.zh-CN.vtt 1.87 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.zh-CN.vtt 1.86 KB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.zh-CN.vtt 1.86 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.en.vtt 1.86 KB
Part 16-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.ar.vtt 1.86 KB
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.en.vtt 1.86 KB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.pt-BR.vtt 1.86 KB
Part 09-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.pt-BR.vtt 1.86 KB
Part 04-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.pt-BR.vtt 1.86 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/10. Time Commitment-d-VfUw7wNEQ.zh-CN.vtt 1.86 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/11. Time Commitment-d-VfUw7wNEQ.zh-CN.vtt 1.86 KB
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.ar.vtt 1.86 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.pt-BR.vtt 1.86 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.en.vtt 1.86 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.pt-BR.vtt 1.86 KB
Part 11-Module 01-Lesson 06_Undoing Changes/01. Undoing Changes - Intro-Kfi7l41wUVc.en.vtt 1.86 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.pt-BR.vtt 1.86 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.pt-BR.vtt 1.86 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.ja.vtt 1.86 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.ja.vtt 1.85 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.en.vtt 1.85 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.ar.vtt 1.85 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.ar.vtt 1.85 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.zh-CN.vtt 1.85 KB
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.pt-BR.vtt 1.85 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.es-ES.vtt 1.85 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.ar.vtt 1.85 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.zh-CN.vtt 1.85 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.en.vtt 1.85 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.ar.vtt 1.85 KB
Part 16-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.pt-BR.vtt 1.84 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.th.vtt 1.84 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.pt-BR.vtt 1.84 KB
Part 07-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.zh-CN.vtt 1.84 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. What are we going to do-rK6YlbBiKQM.zh-CN.vtt 1.84 KB
Part 08-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.en.vtt 1.84 KB
Part 07-Module 01-Lesson 01_What is EDA/03. Go Exploring-dias-YUpewk.zh-CN.vtt 1.84 KB
Part 15-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.en-US.vtt 1.84 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.ar.vtt 1.84 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/10. The Completed Program-yGDHoIOfwt8.zh-CN.vtt 1.84 KB
Part 03-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.pt-BR.vtt 1.84 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.pt-BR.vtt 1.84 KB
Part 08-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.zh-CN.vtt 1.84 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/44. OR Statement-DRmkKVhe6-s.pt-BR.vtt 1.84 KB
Part 16-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.zh-CN.vtt 1.84 KB
Part 15-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.en.vtt 1.84 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.es-MX.vtt 1.84 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.ar.vtt 1.83 KB
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.pt-BR.vtt 1.83 KB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.pt-BR.vtt 1.83 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.ar.vtt 1.83 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.pt-BR.vtt 1.83 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.zh-CN.vtt 1.83 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/01. Adding Commits To A Repo - Intro-sLcOFQ4mGvo.zh-CN.vtt 1.83 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/19. Order By Part II-XQCjREdOqwE.zh-CN.vtt 1.83 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.pt-BR.vtt 1.83 KB
Part 16-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.en.vtt 1.83 KB
Part 03-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.zh-CN.vtt 1.83 KB
Part 09-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.en.vtt 1.83 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/13. LIMIT Statement-cCPHNNhBgpQ.en.vtt 1.82 KB
Part 15-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.en-US.vtt 1.82 KB
Part 03-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.en.vtt 1.82 KB
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.ja.vtt 1.82 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.ar.vtt 1.82 KB
Part 07-Module 01-Lesson 01_What is EDA/05. Aude's Interest in Data-DDNSMG_RltY.ja.vtt 1.82 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.zh-CN.vtt 1.82 KB
Part 15-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.en.vtt 1.82 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.en.vtt 1.82 KB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.ar.vtt 1.82 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.ar.vtt 1.82 KB
Part 16-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.zh-CN.vtt 1.82 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.en.vtt 1.82 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.en.vtt 1.82 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. What are we going to do-rK6YlbBiKQM.pt-BR.vtt 1.82 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/02. What's Ahead-ggbCydfI1JM.zh-CN.vtt 1.82 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.pt-BR.vtt 1.82 KB
Part 11-Module 01-Lesson 02_Create A Git Repo/01. Creating New Repositories - Intro-KT163BkqIeg.en.vtt 1.82 KB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.en.vtt 1.82 KB
Part 16-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.zh-CN.vtt 1.81 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.ar.vtt 1.81 KB
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.pt-BR.vtt 1.81 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.en.vtt 1.81 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/10. Traditional Confidence Interval Methods-DmZwYHuz2eM.pt-BR.vtt 1.81 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.pt-BR.vtt 1.81 KB
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.ar.vtt 1.81 KB
Part 07-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.zh-CN.vtt 1.81 KB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.pt-BR.vtt 1.81 KB
Part 18-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.zh-CN.vtt 1.81 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/20. Connecting Errors and P-Values-hFNjd5l9CLs.zh-CN.vtt 1.81 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/01. Tagging, Branching, And Merging - Intro-sMf_r4_z-Ls.en.vtt 1.81 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.pt-BR.vtt 1.81 KB
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.pt-BR.vtt 1.81 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.zh-CN.vtt 1.81 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.ar.vtt 1.81 KB
Part 16-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.zh-CN.vtt 1.81 KB
Part 03-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.pt-BR.vtt 1.81 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.es-MX.vtt 1.81 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.es-MX.vtt 1.81 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.es-MX.vtt 1.81 KB
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.th.vtt 1.81 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.ar.vtt 1.81 KB
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.en.vtt 1.8 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.pt-BR.vtt 1.8 KB
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.zh-CN.vtt 1.8 KB
Part 04-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.pt-BR.vtt 1.8 KB
Part 07-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.pt-BR.vtt 1.8 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.pt-BR.vtt 1.8 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/06. Types Of Errors - Part I-aw6GMxIvENc.zh-CN.vtt 1.8 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.pt-BR.vtt 1.8 KB
Part 07-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.zh-CN.vtt 1.8 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.ar.vtt 1.8 KB
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.en.vtt 1.8 KB
Part 03-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.ar.vtt 1.8 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/06. How Databases Store Data-H0C9z_sRvLE.ar.vtt 1.8 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 71 Merging-gQiWicrreJg.en.vtt 1.8 KB
Part 09-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.zh-CN.vtt 1.79 KB
Part 15-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.pt-BR.vtt 1.79 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.zh-CN.vtt 1.79 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/16. ORDER BY Statement-wqj2As31LqI.zh-CN.vtt 1.79 KB
Part 03-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.zh-CN.vtt 1.79 KB
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Part 09-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.zh-CN.vtt 1.76 KB
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Part 07-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.pt-BR.vtt 1.76 KB
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Part 04-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.zh-CN.vtt 1.75 KB
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Part 16-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.ar.vtt 1.75 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.en.vtt 1.75 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/02. Projects Term 1 V2-1e1y6QB34YM.zh-CN.vtt 1.75 KB
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Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.en.vtt 1.75 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.pt-BR.vtt 1.75 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.zh-CN.vtt 1.75 KB
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.ar.vtt 1.75 KB
Part 07-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.pt-BR.vtt 1.75 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/21. Conclusions In Hypothesis Testing-I0Mo7hcxahY.zh-CN.vtt 1.75 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.en.vtt 1.75 KB
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Part 16-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.en.vtt 1.75 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.en.vtt 1.75 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.ar.vtt 1.75 KB
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.ar.vtt 1.75 KB
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Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.pt-BR.vtt 1.75 KB
Part 15-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.zh-CN.vtt 1.75 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.pt-BR.vtt 1.74 KB
Part 18-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.zh-CN.vtt 1.74 KB
Part 08-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.pt-BR.vtt 1.74 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.zh-CN.vtt 1.74 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.ja.vtt 1.74 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-3kH4ei9l4h8.ja.vtt 1.74 KB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.pt-BR.vtt 1.74 KB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.pt-BR.vtt 1.74 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.es-ES.vtt 1.74 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.zh-CN.vtt 1.74 KB
Part 18-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.ar.vtt 1.74 KB
Part 07-Module 01-Lesson 01_What is EDA/10. Course Overview-W8N0aSMPff8.ja.vtt 1.74 KB
Part 08-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.ar.vtt 1.73 KB
Part 04-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.en.vtt 1.73 KB
Part 16-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.ja.vtt 1.73 KB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.pt-BR.vtt 1.73 KB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.ja.vtt 1.73 KB
Part 16-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.en.vtt 1.73 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.en.vtt 1.73 KB
Part 15-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.pt-BR.vtt 1.73 KB
Part 16-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.ar.vtt 1.73 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.ar.vtt 1.73 KB
Part 04-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.ar.vtt 1.73 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.pt-BR.vtt 1.73 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.pt-BR.vtt 1.73 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.pt-BR.vtt 1.73 KB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.es-ES.vtt 1.72 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.pt-BR.vtt 1.72 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.ar.vtt 1.72 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-MV_e0z9kFjM.en.vtt 1.72 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.en.vtt 1.72 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.en.vtt 1.72 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/04. Ud1110 IntroPy L5 22 Continue Crawl Solution-tLhTfSZ6LRA.ar.vtt 1.72 KB
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.zh-CN.vtt 1.72 KB
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.en.vtt 1.72 KB
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.zh-CN.vtt 1.72 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.en.vtt 1.72 KB
Part 04-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.zh-CN.vtt 1.72 KB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.en.vtt 1.72 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.pt-BR.vtt 1.71 KB
Part 04-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.zh-CN.vtt 1.71 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-3kH4ei9l4h8.en.vtt 1.71 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.pt-BR.vtt 1.71 KB
Part 03-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.pt-BR.vtt 1.71 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/07. Types Of Statements-vLvJbIz94C4.pt-BR.vtt 1.71 KB
Part 16-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.zh-CN.vtt 1.71 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.pt-BR.vtt 1.71 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.pt-BR.vtt 1.71 KB
Part 11-Module 01-Lesson 06_Undoing Changes/01. Undoing Changes - Intro-Kfi7l41wUVc.pt-BR.vtt 1.71 KB
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.en.vtt 1.71 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.en.vtt 1.71 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.pt-BR.vtt 1.71 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.en.vtt 1.71 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.en.vtt 1.71 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/01. Welcome!-KJT4Z0xpHns.zh-CN.vtt 1.71 KB
Part 07-Module 01-Lesson 01_What is EDA/10. Course Overview-W8N0aSMPff8.pt-BR.vtt 1.71 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.ja.vtt 1.71 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.ja.vtt 1.71 KB
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.zh-CN.vtt 1.71 KB
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.zh-CN.vtt 1.71 KB
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.ar.vtt 1.71 KB
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.zh-CN.vtt 1.71 KB
Part 04-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.zh-CN.vtt 1.7 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.pt-BR.vtt 1.7 KB
Part 18-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.ar.vtt 1.7 KB
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.ar.vtt 1.7 KB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.ar.vtt 1.7 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/26. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.en.vtt 1.7 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 11 Git Log Output Explained-xJfurQcVYfo.en.vtt 1.7 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.ja.vtt 1.7 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.en.vtt 1.7 KB
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.zh-CN.vtt 1.7 KB
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.pt-BR.vtt 1.7 KB
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Part 08-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.en.vtt 1.7 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.en.vtt 1.7 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.ja.vtt 1.7 KB
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Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.ja.vtt 1.7 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.en.vtt 1.69 KB
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Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.zh-CN.vtt 1.68 KB
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.zh-CN.vtt 1.68 KB
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Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.ar.vtt 1.68 KB
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Part 04-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.en.vtt 1.67 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/07. Integrity and Mindset-zCOr3O50gQM.ar.vtt 1.67 KB
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Part 09-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.en.vtt 1.67 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.en.vtt 1.67 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.en.vtt 1.67 KB
Part 16-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.pt-BR.vtt 1.67 KB
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Part 16-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.en.vtt 1.66 KB
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Part 08-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.en.vtt 1.65 KB
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Part 03-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.zh-CN.vtt 1.65 KB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.zh-CN.vtt 1.65 KB
Part 16-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.zh-CN.vtt 1.65 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/03. Parch Posey Database-JOMI560DgXg.ar.vtt 1.65 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.ar.vtt 1.65 KB
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Part 16-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.pt-BR.vtt 1.65 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.pt-BR.vtt 1.64 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.zh-CN.vtt 1.64 KB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.th.vtt 1.64 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.en.vtt 1.64 KB
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.pt-BR.vtt 1.64 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.it.vtt 1.64 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.zh-CN.vtt 1.64 KB
Part 07-Module 01-Lesson 01_What is EDA/05. Aude's Interest in Data-DDNSMG_RltY.zh-CN.vtt 1.64 KB
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.pt-BR.vtt 1.64 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 1-APRpwqFpGwI.en.vtt 1.64 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.pt-BR.vtt 1.64 KB
Part 18-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.zh-CN.vtt 1.64 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/12. Ud1110 IntroPy L237 Break Up Your Code Ideas-qrp8r48BPUs.en.vtt 1.63 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.en.vtt 1.63 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.pt-BR.vtt 1.63 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.zh-CN.vtt 1.63 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.en.vtt 1.63 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.pt-BR.vtt 1.63 KB
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.en.vtt 1.63 KB
Part 11-Module 01-Lesson 01_What is Version Control/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 11 Google Docs Revision History Walkthrough-GcvvbdKEchk.en.vtt 1.63 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.ar.vtt 1.63 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.ar.vtt 1.63 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.ar.vtt 1.63 KB
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.zh-CN.vtt 1.63 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.pt-BR.vtt 1.63 KB
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.ar.vtt 1.63 KB
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Part 16-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.ar.vtt 1.63 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.pt-BR.vtt 1.63 KB
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Part 16-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.zh-CN.vtt 1.63 KB
Part 07-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.zh-CN.vtt 1.63 KB
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.pt-BR.vtt 1.62 KB
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Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.zh-CN.vtt 1.62 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.ar.vtt 1.62 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.ar.vtt 1.62 KB
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Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.ja.vtt 1.62 KB
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.pt-BR.vtt 1.62 KB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.en.vtt 1.62 KB
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.ja.vtt 1.62 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.pt-BR.vtt 1.62 KB
Part 12-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.zh-CN.vtt 1.62 KB
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.ar.vtt 1.62 KB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.ar.vtt 1.62 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 37 Squashing Bugs-X-GqfxYpaw0.ar.vtt 1.61 KB
Part 08-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.pt-BR.vtt 1.61 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.ja.vtt 1.61 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.ja.vtt 1.61 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.zh-CN.vtt 1.61 KB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.en.vtt 1.61 KB
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Part 08-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.ar.vtt 1.61 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.pt-BR.vtt 1.61 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.zh-CN.vtt 1.61 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.ar.vtt 1.61 KB
Part 16-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.pt-BR.vtt 1.61 KB
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Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.en.vtt 1.61 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.en.vtt 1.61 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.pt-BR.vtt 1.61 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.zh-CN.vtt 1.6 KB
Part 16-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.en.vtt 1.6 KB
Part 18-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.zh-CN.vtt 1.6 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.zh-CN.vtt 1.6 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.ja.vtt 1.6 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.ar.vtt 1.6 KB
Part 09-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.en.vtt 1.6 KB
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Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.pt-BR.vtt 1.6 KB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.en.vtt 1.6 KB
Part 18-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.ar.vtt 1.6 KB
Part 09-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.pt-BR.vtt 1.6 KB
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Part 14-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.pt-BR.vtt 1.6 KB
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.en.vtt 1.6 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.pt-BR.vtt 1.6 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.en.vtt 1.6 KB
Part 18-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.zh-CN.vtt 1.6 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 27 Confession Corner-xtsugblSwrU.en.vtt 1.6 KB
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.th.vtt 1.6 KB
Part 15-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.zh-CN.vtt 1.6 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.zh-CN.vtt 1.59 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/13. LIMIT Statement-cCPHNNhBgpQ.zh-CN.vtt 1.59 KB
Part 15-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.zh-CN.vtt 1.59 KB
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.ar.vtt 1.59 KB
Part 03-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.zh-CN.vtt 1.59 KB
Part 08-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.en.vtt 1.59 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.en.vtt 1.59 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.zh-CN.vtt 1.59 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.zh-CN.vtt 1.59 KB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.ar.vtt 1.59 KB
Part 04-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.ja.vtt 1.59 KB
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.ja.vtt 1.59 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.zh-CN.vtt 1.59 KB
Part 16-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.ja.vtt 1.59 KB
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.ar.vtt 1.59 KB
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.ar.vtt 1.59 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.ja.vtt 1.59 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.zh-CN.vtt 1.59 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 03 Tagging Overview-D4VdXT72ASE.zh-CN.vtt 1.59 KB
Part 04-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.en.vtt 1.59 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.zh-CN.vtt 1.59 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.en.vtt 1.59 KB
Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.ar.vtt 1.58 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.en.vtt 1.58 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.pt-BR.vtt 1.58 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/07. Projects and Progress-Z9ZLMQWsbsk.ar.vtt 1.58 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.en.vtt 1.58 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.en.vtt 1.58 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.ja.vtt 1.58 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/06. Projects and Progress-Z9ZLMQWsbsk.ar.vtt 1.58 KB
Part 16-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.pt-BR.vtt 1.58 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.pt-BR.vtt 1.58 KB
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.pt-BR.vtt 1.58 KB
Part 16-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.pt-BR.vtt 1.58 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/01. Tagging, Branching, And Merging - Intro-sMf_r4_z-Ls.pt-BR.vtt 1.58 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.en-US.vtt 1.58 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.pt-BR.vtt 1.58 KB
Part 07-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.ja.vtt 1.58 KB
Part 16-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.zh-CN.vtt 1.58 KB
Part 12-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.en.vtt 1.58 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.en.vtt 1.57 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/12. Ud1110 IntroPy L237 Break Up Your Code Ideas-qrp8r48BPUs.pt-BR.vtt 1.57 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.en.vtt 1.57 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.pt-BR.vtt 1.57 KB
Part 08-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.en.vtt 1.57 KB
Part 03-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.pt-BR.vtt 1.57 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/35. IN Operator-_JPO7wwX3uA.pt-BR.vtt 1.57 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 17 Git The Big Picture 2-rFtUkk-sCqw.ar.vtt 1.57 KB
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.ar.vtt 1.57 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.pt-BR.vtt 1.57 KB
Part 07-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.zh-CN.vtt 1.57 KB
Part 07-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.pt-BR.vtt 1.57 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 18 Recap-xqD9ImXXXHk.pt-BR.vtt 1.57 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Python Documentation-lBtG0DO_KqM.ar.vtt 1.57 KB
Part 16-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.en.vtt 1.57 KB
Part 16-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.ar.vtt 1.57 KB
Part 08-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.en.vtt 1.57 KB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.zh-CN.vtt 1.57 KB
Part 08-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.zh-CN.vtt 1.57 KB
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.zh-CN.vtt 1.56 KB
Part 15-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-wkWDrSBBtz0.en.vtt 1.56 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.en.vtt 1.56 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/07. Ud1110 IntroPy L5 30 Finding The First Link-Z-uuXDrMzqM.en.vtt 1.56 KB
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.pt-BR.vtt 1.56 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.zh-CN.vtt 1.56 KB
Part 07-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.en.vtt 1.56 KB
Part 16-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.en.vtt 1.56 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.en.vtt 1.56 KB
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.ar.vtt 1.56 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.ar.vtt 1.56 KB
Part 07-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.en.vtt 1.56 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.zh-CN.vtt 1.56 KB
Part 07-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.en.vtt 1.56 KB
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.pt-BR.vtt 1.56 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.pt-BR.vtt 1.56 KB
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.pt-BR.vtt 1.56 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.pt-BR.vtt 1.55 KB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.zh-CN.vtt 1.55 KB
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.ar.vtt 1.55 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.ar.vtt 1.55 KB
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.en.vtt 1.55 KB
Part 03-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.pt-BR.vtt 1.55 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.es-ES.vtt 1.55 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/02. Introduction-Z8WNfx9Oq9s.pt-BR.vtt 1.55 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.zh-CN.vtt 1.55 KB
Part 16-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.en.vtt 1.55 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/07. Outro-5eyvsMvAPYs.ar.vtt 1.55 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.zh-CN.vtt 1.55 KB
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.zh-CN.vtt 1.55 KB
Part 16-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.pt-BR.vtt 1.55 KB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.ar.vtt 1.55 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.pt-BR.vtt 1.54 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.pt-BR.vtt 1.54 KB
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.th.vtt 1.54 KB
Part 18-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.pt-BR.vtt 1.54 KB
Part 16-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.pt-BR.vtt 1.54 KB
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.zh-CN.vtt 1.54 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.en.vtt 1.54 KB
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.pt-BR.vtt 1.54 KB
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.en.vtt 1.54 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 1-APRpwqFpGwI.pt-BR.vtt 1.54 KB
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.pt-BR.vtt 1.54 KB
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.ja.vtt 1.54 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.en.vtt 1.54 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 03 Tagging Overview-D4VdXT72ASE.pt-BR.vtt 1.54 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.en.vtt 1.54 KB
Part 18-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.ar.vtt 1.54 KB
Part 07-Module 01-Lesson 01_What is EDA/08. Our Approach for This Course-dBsf-szQ00s.en.vtt 1.54 KB
Part 16-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.ar.vtt 1.54 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.ar.vtt 1.54 KB
Part 15-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.en.vtt 1.54 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.en.vtt 1.54 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.zh-CN.vtt 1.54 KB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.pt-BR.vtt 1.53 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.ja.vtt 1.53 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.pt-BR.vtt 1.53 KB
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.ar.vtt 1.53 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.zh-CN.vtt 1.53 KB
Part 04-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.zh-CN.vtt 1.53 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.ar.vtt 1.53 KB
Part 04-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.zh-CN.vtt 1.53 KB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.ar.vtt 1.53 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.ar.vtt 1.53 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.pt-BR.vtt 1.53 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.en.vtt 1.53 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.pt-BR.vtt 1.53 KB
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.es-ES.vtt 1.53 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.ar.vtt 1.53 KB
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.ja.vtt 1.52 KB
Part 15-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.pt-BR.vtt 1.52 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.zh-CN.vtt 1.52 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.en-US.vtt 1.52 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.pt-BR.vtt 1.52 KB
Part 09-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.zh-CN.vtt 1.52 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.en-US.vtt 1.52 KB
Part 15-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.zh-CN.vtt 1.52 KB
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.en.vtt 1.52 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.en.vtt 1.52 KB
Part 16-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.zh-CN.vtt 1.52 KB
Part 08-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.zh-CN.vtt 1.52 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.zh-CN.vtt 1.52 KB
Part 15-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.zh-CN.vtt 1.52 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-MV_e0z9kFjM.zh-CN.vtt 1.52 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.pt-BR.vtt 1.52 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.en.vtt 1.52 KB
Part 16-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.zh-CN.vtt 1.52 KB
Part 08-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.zh-CN.vtt 1.52 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 18 Recap-xqD9ImXXXHk.en.vtt 1.52 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.en.vtt 1.52 KB
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.en-US.vtt 1.52 KB
Part 08-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.zh-CN.vtt 1.52 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.en.vtt 1.52 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.es-MX.vtt 1.52 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.ar.vtt 1.51 KB
Part 09-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.en.vtt 1.51 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.pt-BR.vtt 1.51 KB
Part 18-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.pt-BR.vtt 1.51 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.ar.vtt 1.51 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/07. ggpairs Function-XUZIGbX3JIg.zh-CN.vtt 1.51 KB
Part 16-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.pt-BR.vtt 1.51 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.ar.vtt 1.51 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/44. OR Statement-DRmkKVhe6-s.zh-CN.vtt 1.51 KB
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.en.vtt 1.51 KB
Part 03-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.zh-CN.vtt 1.51 KB
Part 16-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.pt-BR.vtt 1.51 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.ar.vtt 1.51 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 11 Git Log Output Explained-xJfurQcVYfo.zh-CN.vtt 1.51 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/12. Ud1110 IntroPy L237 Break Up Your Code Ideas-qrp8r48BPUs.zh-CN.vtt 1.51 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.en.vtt 1.51 KB
Part 04-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.en.vtt 1.5 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 1-APRpwqFpGwI.zh-CN.vtt 1.5 KB
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.en.vtt 1.5 KB
Part 12-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.ar.vtt 1.5 KB
Part 04-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.pt-BR.vtt 1.5 KB
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.zh-CN.vtt 1.5 KB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.en.vtt 1.5 KB
Part 04-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.pt-BR.vtt 1.5 KB
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.en.vtt 1.5 KB
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.ar.vtt 1.5 KB
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.en-US.vtt 1.5 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-3kH4ei9l4h8.zh-CN.vtt 1.5 KB
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.ar.vtt 1.5 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.hr.vtt 1.5 KB
Part 16-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.zh-CN.vtt 1.5 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.pt-BR.vtt 1.5 KB
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.ar.vtt 1.5 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.ja.vtt 1.5 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.zh-CN.vtt 1.5 KB
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.pt-BR.vtt 1.5 KB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.ja.vtt 1.5 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.zh-CN.vtt 1.5 KB
Part 16-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.pt-BR.vtt 1.5 KB
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.pt-BR.vtt 1.5 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/04. Entity Relationship Diagrams-YY2TAJLEINA.ar.vtt 1.49 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/01. Welcome To DAND Term 2-OOcC8OUJmc0.zh-CN.vtt 1.49 KB
Part 03-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.ar.vtt 1.49 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/08. Ud1110 IntroPy L3 37 Reading Existing Code-0Pg3HryU9Z4.en.vtt 1.49 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.pt-BR.vtt 1.49 KB
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.en.vtt 1.49 KB
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.ja.vtt 1.49 KB
Part 07-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.zh-CN.vtt 1.49 KB
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.pt-BR.vtt 1.49 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.pt-BR.vtt 1.49 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.en.vtt 1.49 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.en.vtt 1.49 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.zh-CN.vtt 1.49 KB
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.ar.vtt 1.49 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.zh-CN.vtt 1.49 KB
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.en.vtt 1.49 KB
Part 03-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.en.vtt 1.49 KB
Part 15-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.pt-BR.vtt 1.49 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.en.vtt 1.49 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/07. Types Of Statements-vLvJbIz94C4.en.vtt 1.49 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.en.vtt 1.49 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.ar.vtt 1.49 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 27 Confession Corner-xtsugblSwrU.zh-CN.vtt 1.49 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/07. Ud1110 IntroPy L5 30 Finding The First Link-Z-uuXDrMzqM.pt-BR.vtt 1.49 KB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.ar.vtt 1.48 KB
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.pt-BR.vtt 1.48 KB
Part 07-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.pt-BR.vtt 1.48 KB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.ja.vtt 1.48 KB
Part 15-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.es-MX.vtt 1.48 KB
Part 16-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.en.vtt 1.48 KB
Part 07-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.zh-CN.vtt 1.48 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.en.vtt 1.48 KB
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.en.vtt 1.48 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.pt-BR.vtt 1.48 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.en.vtt 1.48 KB
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.en.vtt 1.48 KB
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.zh-CN.vtt 1.48 KB
Part 04-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.en.vtt 1.48 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.en.vtt 1.48 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.zh-CN.vtt 1.48 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.pt-BR.vtt 1.48 KB
Part 12-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.pt-BR.vtt 1.48 KB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.zh-CN.vtt 1.47 KB
Part 16-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.zh-CN.vtt 1.47 KB
Part 03-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.en.vtt 1.47 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/35. IN Operator-_JPO7wwX3uA.en.vtt 1.47 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.zh-CN.vtt 1.47 KB
Part 04-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.zh-CN.vtt 1.47 KB
Part 08-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.zh-CN.vtt 1.47 KB
Part 16-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.pt-BR.vtt 1.47 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.en.vtt 1.47 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.pt-BR.vtt 1.47 KB
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.pt-BR.vtt 1.47 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.en.vtt 1.47 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.en.vtt 1.47 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/07. A Repository's History - Outro-9rUf2HbdAd8.ar.vtt 1.47 KB
Part 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.ar.vtt 1.47 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.ar.vtt 1.47 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.zh-CN.vtt 1.46 KB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.ar.vtt 1.46 KB
Part 12-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.en.vtt 1.46 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.ar.vtt 1.46 KB
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.zh-CN.vtt 1.46 KB
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.ja.vtt 1.46 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.pt-BR.vtt 1.46 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 25 Git Log Vs Git Log --Oneline Walkthru-rn6v_QgYFnU.ar.vtt 1.46 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.pt-BR.vtt 1.46 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.ja.vtt 1.46 KB
Part 16-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.pt-BR.vtt 1.46 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.ar.vtt 1.46 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.pt-BR.vtt 1.46 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.zh-CN.vtt 1.46 KB
Part 08-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.pt-BR.vtt 1.46 KB
Part 16-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.en.vtt 1.46 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.en.vtt 1.46 KB
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.zh-CN.vtt 1.46 KB
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.ar.vtt 1.46 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/01. Intro Project Explore Weather Trends-xneztkf0TsY.ar.vtt 1.46 KB
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.ar.vtt 1.46 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.ar.vtt 1.46 KB
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.zh-CN.vtt 1.45 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. INTRODUÇÃO AO PROJETO PRINCIPAL V2---9IFCNBM6Y.pt-BR.vtt 1.45 KB
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.en.vtt 1.45 KB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.pt-BR.vtt 1.45 KB
Part 07-Module 01-Lesson 01_What is EDA/02. Data is Ubiquitous-ieiQqLicBjg.ja.vtt 1.45 KB
Part 11-Module 01-Lesson 01_What is Version Control/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 11 Google Docs Revision History Walkthrough-GcvvbdKEchk.zh-CN.vtt 1.45 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.pt-BR.vtt 1.45 KB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.ar.vtt 1.45 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.zh-CN.vtt 1.45 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.ja.vtt 1.45 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.ar.vtt 1.45 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.ar.vtt 1.45 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.pt-BR.vtt 1.45 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.pt-BR.vtt 1.45 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.es-ES.vtt 1.45 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.en.vtt 1.45 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.zh-CN.vtt 1.45 KB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.ar.vtt 1.45 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.ar.vtt 1.45 KB
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.pt-BR.vtt 1.45 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.ja.vtt 1.45 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.zh-CN.vtt 1.45 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.ja.vtt 1.44 KB
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.zh-CN.vtt 1.44 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/26. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.zh-CN.vtt 1.44 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.en.vtt 1.44 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.es-ES.vtt 1.44 KB
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.ar.vtt 1.44 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.en.vtt 1.44 KB
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.ar.vtt 1.44 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.en.vtt 1.44 KB
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.ar.vtt 1.44 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.zh-CN.vtt 1.44 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/07. Ud1110 IntroPy L5 30 Finding The First Link-Z-uuXDrMzqM.zh-CN.vtt 1.44 KB
Part 16-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.zh-CN.vtt 1.43 KB
Part 11-Module 01-Lesson 01_What is Version Control/06. Onward-iXbMaTwfIJI.ar.vtt 1.43 KB
Part 09-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.zh-CN.vtt 1.43 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.ja.vtt 1.43 KB
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.zh-CN.vtt 1.43 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.en.vtt 1.43 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.es-MX.vtt 1.43 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.pt-BR.vtt 1.43 KB
Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.ar.vtt 1.43 KB
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.zh-CN.vtt 1.43 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.zh-CN.vtt 1.43 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.en.vtt 1.43 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.en.vtt 1.43 KB
Part 08-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.en.vtt 1.43 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.en.vtt 1.43 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.zh-CN.vtt 1.43 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.zh-CN.vtt 1.43 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.zh-CN.vtt 1.43 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.en.vtt 1.43 KB
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.en.vtt 1.43 KB
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.en.vtt 1.43 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.en.vtt 1.43 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.en.vtt 1.43 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/07. Outro-ot4fPX1jzOI.ar.vtt 1.43 KB
Part 07-Module 01-Lesson 01_What is EDA/08. Our Approach for This Course-dBsf-szQ00s.ja.vtt 1.43 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.ar.vtt 1.42 KB
Part 15-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.zh-CN.vtt 1.42 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.pt-BR.vtt 1.42 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.it.vtt 1.42 KB
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.ar.vtt 1.42 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.ar.vtt 1.42 KB
Part 04-Module 01-Lesson 16_Logistic Regression/01. Introduction to Logistic Regression-P_f2RjjnPEg.zh-CN.vtt 1.42 KB
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.en.vtt 1.42 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.pt-BR.vtt 1.42 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.pt-BR.vtt 1.42 KB
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.en.vtt 1.42 KB
Part 16-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.ar.vtt 1.42 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.en.vtt 1.42 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.en.vtt 1.42 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.en.vtt 1.42 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.pt-BR.vtt 1.42 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.ar.vtt 1.42 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/08. Ud1110 IntroPy L3 37 Reading Existing Code-0Pg3HryU9Z4.zh-CN.vtt 1.42 KB
Part 16-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.en.vtt 1.42 KB
Part 03-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.ar.vtt 1.42 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/25. WHERE with Non-Numeric Data-_pLx7MHOyjo.ar.vtt 1.42 KB
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.pt-BR.vtt 1.42 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.ar.vtt 1.42 KB
Part 18-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.ar.vtt 1.42 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.zh-CN.vtt 1.41 KB
Part 07-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.zh-CN.vtt 1.41 KB
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.zh-CN.vtt 1.41 KB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.pt-BR.vtt 1.41 KB
Part 07-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.ja.vtt 1.41 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.pt-BR.vtt 1.41 KB
Part 16-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.ar.vtt 1.41 KB
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.ar.vtt 1.41 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.en.vtt 1.41 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.ar.vtt 1.41 KB
Part 16-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.pt-BR.vtt 1.41 KB
Part 16-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.en.vtt 1.41 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.es-ES.vtt 1.41 KB
Part 16-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.pt-BR.vtt 1.41 KB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.en.vtt 1.41 KB
Part 16-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.pt-BR.vtt 1.41 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.pt-BR.vtt 1.41 KB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.pt-BR.vtt 1.41 KB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.en.vtt 1.4 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.pt-BR.vtt 1.4 KB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.ja.vtt 1.4 KB
Part 13-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.pt-BR.vtt 1.4 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.en.vtt 1.4 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.en.vtt 1.4 KB
Part 03-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.zh-CN.vtt 1.4 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.en.vtt 1.4 KB
Part 07-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.zh-CN.vtt 1.4 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/07. Outro-5eyvsMvAPYs.pt-BR.vtt 1.39 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.ar.vtt 1.39 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.zh-CN.vtt 1.39 KB
Part 12-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.en.vtt 1.39 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.ja.vtt 1.39 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.en.vtt 1.39 KB
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.ar.vtt 1.39 KB
Part 18-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.pt-BR.vtt 1.39 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.pt-BR.vtt 1.39 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.ar.vtt 1.39 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.zh-CN.vtt 1.39 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.en.vtt 1.39 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.ar.vtt 1.39 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.en.vtt 1.39 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.en.vtt 1.39 KB
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Part 09-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.en.vtt 1.38 KB
Part 04-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.zh-CN.vtt 1.38 KB
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Part 18-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.en.vtt 1.38 KB
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Part 04-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.zh-CN.vtt 1.38 KB
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Part 03-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.pt-BR.vtt 1.38 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/06. How Databases Store Data-H0C9z_sRvLE.pt-BR.vtt 1.38 KB
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Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.pt-BR.vtt 1.38 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.en.vtt 1.38 KB
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Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.zh-CN.vtt 1.38 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/02. Ud1110 IntroPy L1 07 Arithmetic Expression In Python-Iq3ovQqBj1M.en.vtt 1.38 KB
Part 16-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.zh-CN.vtt 1.38 KB
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Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.ja.vtt 1.38 KB
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.zh-CN.vtt 1.37 KB
Part 16-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.ar.vtt 1.37 KB
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Part 04-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.ar.vtt 1.37 KB
Part 16-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.en.vtt 1.37 KB
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Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.en.vtt 1.37 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.zh-CN.vtt 1.37 KB
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Part 04-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.ar.vtt 1.37 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.ar.vtt 1.37 KB
Part 08-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.zh-CN.vtt 1.37 KB
Part 07-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.ar.vtt 1.37 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.pt-BR.vtt 1.37 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/10. Traditional Confidence Interval Methods-DmZwYHuz2eM.zh-CN.vtt 1.37 KB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.pt-BR.vtt 1.37 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.zh-CN.vtt 1.37 KB
Part 16-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.pt-BR.vtt 1.37 KB
Part 04-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.pt-BR.vtt 1.37 KB
Part 15-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-wkWDrSBBtz0.pt-BR.vtt 1.37 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.zh-CN.vtt 1.37 KB
Part 16-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video-68EGMItJiNM.ar.vtt 1.36 KB
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Part 07-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.pt-BR.vtt 1.36 KB
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.ja.vtt 1.36 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/08. How Does Project Submission Work-jCJa_VP6qgg.ar.vtt 1.36 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/09. How Does Project Submission Work-jCJa_VP6qgg.ar.vtt 1.36 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.hr.vtt 1.36 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.zh-CN.vtt 1.36 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.en.vtt 1.36 KB
Part 08-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.en.vtt 1.36 KB
Part 15-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.zh-CN.vtt 1.36 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.pt-BR.vtt 1.36 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.pt-BR.vtt 1.36 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.ja.vtt 1.36 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.pt-BR.vtt 1.36 KB
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.pt-BR.vtt 1.36 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.zh-CN.vtt 1.36 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 18 Recap-xqD9ImXXXHk.zh-CN.vtt 1.35 KB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.pt-BR.vtt 1.35 KB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.pt-BR.vtt 1.35 KB
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.ja.vtt 1.35 KB
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.ar.vtt 1.35 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/03. Parch Posey Database-JOMI560DgXg.pt-BR.vtt 1.35 KB
Part 03-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.pt-BR.vtt 1.35 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.pt-BR.vtt 1.35 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.en.vtt 1.35 KB
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.pt-BR.vtt 1.35 KB
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.zh-CN.vtt 1.35 KB
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.pt-BR.vtt 1.35 KB
Part 03-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.en.vtt 1.35 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/02. Introduction-Z8WNfx9Oq9s.en.vtt 1.35 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.pt-BR.vtt 1.35 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.zh-CN.vtt 1.35 KB
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.ar.vtt 1.35 KB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.en.vtt 1.35 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.es-ES.vtt 1.35 KB
Part 16-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.en.vtt 1.35 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.ar.vtt 1.35 KB
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Part 07-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.zh-CN.vtt 1.35 KB
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.pt-BR.vtt 1.35 KB
Part 07-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.zh-CN.vtt 1.35 KB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.es-ES.vtt 1.34 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.ja.vtt 1.34 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.ja.vtt 1.34 KB
Part 04-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.en.vtt 1.34 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.pt-BR.vtt 1.34 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.zh-CN.vtt 1.34 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.ja.vtt 1.34 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.zh-CN.vtt 1.34 KB
Part 12-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.en.vtt 1.34 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/07. Integrity and Mindset-zCOr3O50gQM.pt-BR.vtt 1.34 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.zh-CN.vtt 1.34 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/08. Integrity and Mindset-zCOr3O50gQM.pt-BR.vtt 1.34 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.zh-CN.vtt 1.34 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.zh-CN.vtt 1.34 KB
Part 16-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.en.vtt 1.34 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.ar.vtt 1.34 KB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.en.vtt 1.34 KB
Part 07-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.zh-CN.vtt 1.34 KB
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.ar.vtt 1.34 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.ar.vtt 1.34 KB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.ar.vtt 1.34 KB
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.ar.vtt 1.33 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.ja.vtt 1.33 KB
Part 04-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.pt-BR.vtt 1.33 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.pt-BR.vtt 1.33 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/07. Outro-5eyvsMvAPYs.en.vtt 1.33 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.ar.vtt 1.33 KB
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.ar.vtt 1.33 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.ja.vtt 1.33 KB
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.ar.vtt 1.33 KB
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.ar.vtt 1.33 KB
Part 03-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.zh-CN.vtt 1.33 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.zh-CN.vtt 1.33 KB
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.ar.vtt 1.33 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.zh-CN.vtt 1.33 KB
Part 09-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.zh-CN.vtt 1.33 KB
Part 08-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.ar.vtt 1.33 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.ar.vtt 1.33 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.ar.vtt 1.32 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.en.vtt 1.32 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.pt-BR.vtt 1.32 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.en.vtt 1.32 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.ar.vtt 1.32 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.en-US.vtt 1.32 KB
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Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.ar.vtt 1.32 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.ja.vtt 1.32 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.ar.vtt 1.32 KB
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.ar.vtt 1.32 KB
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.zh-CN.vtt 1.32 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.en.vtt 1.32 KB
Part 16-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.zh-CN.vtt 1.32 KB
Part 04-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.es-ES.vtt 1.32 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 3-oVGmi4zBOT8.ar.vtt 1.32 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.en.vtt 1.32 KB
Part 16-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.zh-CN.vtt 1.32 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/07. Types Of Statements-vLvJbIz94C4.zh-CN.vtt 1.32 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.zh-CN.vtt 1.32 KB
Part 03-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.zh-CN.vtt 1.32 KB
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.ar.vtt 1.32 KB
Part 16-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.en.vtt 1.32 KB
Part 08-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.pt-BR.vtt 1.32 KB
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.ar.vtt 1.32 KB
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.zh-CN.vtt 1.31 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.en-US.vtt 1.31 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. INTRODUÇÃO AO PROJETO PRINCIPAL V2---9IFCNBM6Y.en.vtt 1.31 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.pt-BR.vtt 1.31 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.ar.vtt 1.31 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.ar.vtt 1.31 KB
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.ar.vtt 1.31 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.en.vtt 1.31 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.ar.vtt 1.31 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.ar.vtt 1.31 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.en.vtt 1.31 KB
Part 07-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.zh-CN.vtt 1.31 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/04. Ud1110 IntroPy L5 22 Continue Crawl Solution-tLhTfSZ6LRA.en.vtt 1.31 KB
Part 16-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.en.vtt 1.31 KB
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.zh-CN.vtt 1.31 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.ja.vtt 1.31 KB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.zh-CN.vtt 1.31 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.en.vtt 1.31 KB
Part 18-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.pt-BR.vtt 1.31 KB
Part 11-Module 01-Lesson 06_Undoing Changes/06. Course Outro-twn_cheqoK8.ar.vtt 1.31 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.ja.vtt 1.31 KB
Part 16-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.en.vtt 1.31 KB
Part 04-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.en.vtt 1.31 KB
Part 04-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.zh-CN.vtt 1.31 KB
Part 12-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.zh-CN.vtt 1.31 KB
Part 08-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.en.vtt 1.3 KB
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.pt-BR.vtt 1.3 KB
Part 07-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.en.vtt 1.3 KB
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.zh-CN.vtt 1.3 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.pt-BR.vtt 1.3 KB
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.pt-BR.vtt 1.3 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/02. Ud1110 IntroPy L1 07 Arithmetic Expression In Python-Iq3ovQqBj1M.zh-CN.vtt 1.3 KB
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.pt-BR.vtt 1.3 KB
Part 12-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.zh-CN.vtt 1.3 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.zh-CN.vtt 1.3 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/02. Introduction-Z8WNfx9Oq9s.zh-CN.vtt 1.3 KB
Part 03-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.zh-CN.vtt 1.3 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.pt-BR.vtt 1.3 KB
Part 15-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.en.vtt 1.3 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.zh-CN.vtt 1.29 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.pt-BR.vtt 1.29 KB
Part 04-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.pt-BR.vtt 1.29 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/01. DAND 01 Congrats V1-QS1jKmZWdTk.pt-BR.vtt 1.29 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.pt-BR.vtt 1.29 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/35. IN Operator-_JPO7wwX3uA.zh-CN.vtt 1.29 KB
Part 03-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.zh-CN.vtt 1.29 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.ar.vtt 1.29 KB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.en.vtt 1.29 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.en.vtt 1.29 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/08. Integrity and Mindset-zCOr3O50gQM.en.vtt 1.29 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/07. Integrity and Mindset-zCOr3O50gQM.en.vtt 1.29 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.zh-CN.vtt 1.29 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.zh-CN.vtt 1.29 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.zh-CN.vtt 1.29 KB
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.pt-BR.vtt 1.29 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.en.vtt 1.29 KB
Part 02-Module 01-Lesson 03_Data Structures and Loops/08. Ud1110 IntroPy L3 37 Reading Existing Code-0Pg3HryU9Z4.pt-BR.vtt 1.29 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.pt-BR.vtt 1.29 KB
Part 16-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.zh-CN.vtt 1.29 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.es-ES.vtt 1.28 KB
Part 16-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.ja.vtt 1.28 KB
Part 16-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.zh-CN.vtt 1.28 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.zh-CN.vtt 1.28 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.pt-BR.vtt 1.28 KB
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.en.vtt 1.28 KB
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.en.vtt 1.28 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.pt-BR.vtt 1.28 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.ar.vtt 1.28 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.en.vtt 1.28 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.it.vtt 1.28 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.zh-CN.vtt 1.28 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.pt-BR.vtt 1.28 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.en.vtt 1.28 KB
Part 08-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.pt-BR.vtt 1.28 KB
Part 16-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.zh-CN.vtt 1.28 KB
Part 16-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.zh-CN.vtt 1.28 KB
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.pt-BR.vtt 1.28 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/06. How Databases Store Data-H0C9z_sRvLE.en.vtt 1.28 KB
Part 03-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.en.vtt 1.28 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.en.vtt 1.28 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.pt-BR.vtt 1.28 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.en.vtt 1.27 KB
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.en.vtt 1.27 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/01. Intro Project Explore Weather Trends-xneztkf0TsY.pt-BR.vtt 1.27 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/07. Projects and Progress-Z9ZLMQWsbsk.pt-BR.vtt 1.27 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/06. Projects and Progress-Z9ZLMQWsbsk.pt-BR.vtt 1.27 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.zh-CN.vtt 1.27 KB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.zh-CN.vtt 1.27 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Python Documentation-lBtG0DO_KqM.en.vtt 1.27 KB
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.pt-BR.vtt 1.27 KB
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.zh-CN.vtt 1.27 KB
Part 03-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.pt-BR.vtt 1.27 KB
Part 04-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.ar.vtt 1.27 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.es-ES.vtt 1.27 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.zh-CN.vtt 1.27 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/04. Ud1110 IntroPy L5 22 Continue Crawl Solution-tLhTfSZ6LRA.pt-BR.vtt 1.27 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/25. WHERE with Non-Numeric Data-_pLx7MHOyjo.pt-BR.vtt 1.27 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.ar.vtt 1.27 KB
Part 16-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.ar.vtt 1.27 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.pt-BR.vtt 1.27 KB
Part 08-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.en.vtt 1.27 KB
Part 02-Module 01-Lesson 04_Files and Modules/10. Ud1110 IntroPy L4 99 Lesson Outro-8AOietAcOLk.ar.vtt 1.27 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.ja.vtt 1.27 KB
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.en.vtt 1.27 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Instructor Introduction Charlie And Phillip-8ar0mETDrZw.ar.vtt 1.27 KB
Part 04-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.zh-CN.vtt 1.27 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.en.vtt 1.27 KB
Part 16-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.ar.vtt 1.27 KB
Part 16-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.ar.vtt 1.27 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.zh-CN.vtt 1.27 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.pt-BR.vtt 1.27 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.en.vtt 1.27 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 33 Git Log Vs Git Log --Stat Walkthru-aOICKP_9xiY.ar.vtt 1.27 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.ar.vtt 1.27 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.ar.vtt 1.26 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/24. Final Thoughts-CNGDocH1k3k.ar.vtt 1.26 KB
Part 08-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.zh-CN.vtt 1.26 KB
Part 08-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.en.vtt 1.26 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.pt-BR.vtt 1.26 KB
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.ar.vtt 1.26 KB
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.en-GB.vtt 1.26 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.zh-CN.vtt 1.26 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.en-US.vtt 1.26 KB
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.ar.vtt 1.26 KB
Part 16-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.ar.vtt 1.26 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.ar.vtt 1.26 KB
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.zh-CN.vtt 1.26 KB
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.zh-CN.vtt 1.26 KB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.en.vtt 1.26 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.pt-BR.vtt 1.26 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.en.vtt 1.26 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.zh-CN.vtt 1.26 KB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.pt-BR.vtt 1.26 KB
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.pt-BR.vtt 1.26 KB
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.zh-CN.vtt 1.26 KB
Part 11-Module 01-Lesson 04_Add Commits To A Repo/07. Outro-5eyvsMvAPYs.zh-CN.vtt 1.25 KB
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.pt-BR.vtt 1.25 KB
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.zh-CN.vtt 1.25 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.zh-CN.vtt 1.25 KB
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.ar.vtt 1.25 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.pt-BR.vtt 1.25 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.ar.vtt 1.25 KB
Part 16-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.pt-BR.vtt 1.25 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.en.vtt 1.25 KB
Part 08-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.pt-BR.vtt 1.25 KB
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.ar.vtt 1.25 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.ar.vtt 1.25 KB
Part 07-Module 01-Lesson 01_What is EDA/08. Our Approach for This Course-dBsf-szQ00s.zh-CN.vtt 1.25 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.zh-CN.vtt 1.25 KB
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.zh-CN.vtt 1.25 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.pt-BR.vtt 1.25 KB
Part 15-Module 02-Lesson 05_Trees/13. BST Complications-pcB0wV7myy4.pt-BR.vtt 1.25 KB
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.ar.vtt 1.25 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.en.vtt 1.25 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.zh-CN.vtt 1.25 KB
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.ar.vtt 1.25 KB
Part 16-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.zh-CN.vtt 1.24 KB
Part 18-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.zh-CN.vtt 1.24 KB
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.en.vtt 1.24 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.zh-CN.vtt 1.24 KB
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.pt-BR.vtt 1.24 KB
Part 07-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.ja.vtt 1.24 KB
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.zh-CN.vtt 1.24 KB
Part 16-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.pt-BR.vtt 1.24 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.zh-CN.vtt 1.24 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.en.vtt 1.24 KB
Part 04-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.en.vtt 1.24 KB
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.ar.vtt 1.24 KB
Part 16-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.en.vtt 1.24 KB
Part 08-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.pt-BR.vtt 1.24 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.zh-CN.vtt 1.24 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.pt-BR.vtt 1.24 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.pt-BR.vtt 1.24 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.en.vtt 1.24 KB
Part 16-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.pt-BR.vtt 1.24 KB
Part 18-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.en.vtt 1.24 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.zh-CN.vtt 1.24 KB
Part 04-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.pt-BR.vtt 1.24 KB
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.en.vtt 1.23 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.zh-CN.vtt 1.23 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.en.vtt 1.23 KB
Part 04-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.zh-CN.vtt 1.23 KB
Part 16-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.zh-CN.vtt 1.23 KB
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Part 07-Module 01-Lesson 01_What is EDA/02. Data is Ubiquitous-ieiQqLicBjg.zh-CN.vtt 1.23 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.ar.vtt 1.23 KB
Part 08-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.ar.vtt 1.23 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.zh-CN.vtt 1.23 KB
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.es-ES.vtt 1.23 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.en.vtt 1.23 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.ar.vtt 1.22 KB
Part 12-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.pt-BR.vtt 1.22 KB
Part 16-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.pt-BR.vtt 1.22 KB
Part 16-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.zh-CN.vtt 1.22 KB
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.zh-CN.vtt 1.22 KB
Part 16-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.zh-CN.vtt 1.22 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.pt-BR.vtt 1.22 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.en.vtt 1.22 KB
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.en.vtt 1.22 KB
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.ar.vtt 1.22 KB
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.zh-CN.vtt 1.22 KB
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.ar.vtt 1.22 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.zh-CN.vtt 1.22 KB
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Part 04-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.ja.vtt 1.22 KB
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.th.vtt 1.22 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 25 Git Log Vs Git Log --Oneline Walkthru-rn6v_QgYFnU.pt-BR.vtt 1.22 KB
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.ja.vtt 1.22 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.ja.vtt 1.22 KB
Part 16-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.ar.vtt 1.22 KB
Part 16-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.zh-CN.vtt 1.22 KB
Part 15-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.pt-BR.vtt 1.21 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/03. Parch Posey Database-JOMI560DgXg.en.vtt 1.21 KB
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.ar.vtt 1.21 KB
Part 03-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.en.vtt 1.21 KB
Part 07-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.ja.vtt 1.21 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.ja.vtt 1.21 KB
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.ar.vtt 1.21 KB
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.en.vtt 1.21 KB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.pt-BR.vtt 1.21 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.pt-BR.vtt 1.21 KB
Part 15-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.es-MX.vtt 1.21 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.ar.vtt 1.21 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.zh-CN.vtt 1.21 KB
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.zh-CN.vtt 1.21 KB
Part 16-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.zh-CN.vtt 1.21 KB
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.it.vtt 1.21 KB
Part 08-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.en.vtt 1.21 KB
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.pt-BR.vtt 1.21 KB
Part 15-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.en-US.vtt 1.21 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.zh-CN.vtt 1.21 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.zh-CN.vtt 1.21 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.ar.vtt 1.21 KB
Part 16-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.ar.vtt 1.21 KB
Part 16-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.zh-CN.vtt 1.21 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.zh-CN.vtt 1.2 KB
Part 15-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.en.vtt 1.2 KB
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.en.vtt 1.2 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/08. Integrity and Mindset-zCOr3O50gQM.zh-CN.vtt 1.2 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/07. Integrity and Mindset-zCOr3O50gQM.zh-CN.vtt 1.2 KB
Part 08-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.zh-CN.vtt 1.2 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.zh-CN.vtt 1.2 KB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.ja.vtt 1.2 KB
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.pt-BR.vtt 1.2 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.pt-BR.vtt 1.2 KB
Part 04-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.en.vtt 1.2 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.en.vtt 1.2 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.en.vtt 1.2 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.zh-CN.vtt 1.2 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.en.vtt 1.19 KB
Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.pt-BR.vtt 1.19 KB
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.zh-CN.vtt 1.19 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.ja.vtt 1.19 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/07. Outro-ot4fPX1jzOI.en.vtt 1.19 KB
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.ar.vtt 1.19 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.en.vtt 1.19 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.zh-CN.vtt 1.19 KB
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.ar.vtt 1.19 KB
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.th.vtt 1.19 KB
Part 03-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.en.vtt 1.19 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.ar.vtt 1.19 KB
Part 15-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.en-US.vtt 1.19 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.ar.vtt 1.19 KB
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.en.vtt 1.19 KB
Part 16-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.zh-CN.vtt 1.19 KB
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.ar.vtt 1.19 KB
Part 16-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.en.vtt 1.19 KB
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.ar.vtt 1.19 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.en.vtt 1.19 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.pt-BR.vtt 1.19 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.zh-CN.vtt 1.19 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.en.vtt 1.19 KB
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. INTRODUÇÃO AO PROJETO PRINCIPAL V2---9IFCNBM6Y.zh-CN.vtt 1.19 KB
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.ja.vtt 1.19 KB
Part 15-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.en.vtt 1.19 KB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.ja.vtt 1.19 KB
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.pt-BR.vtt 1.18 KB
Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.ja.vtt 1.18 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.en.vtt 1.18 KB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.en.vtt 1.18 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/06. How Databases Store Data-H0C9z_sRvLE.zh-CN.vtt 1.18 KB
Part 03-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.zh-CN.vtt 1.18 KB
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.en.vtt 1.18 KB
Part 08-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.zh-CN.vtt 1.18 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.en.vtt 1.18 KB
Part 16-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.pt-BR.vtt 1.18 KB
Part 12-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.zh-CN.vtt 1.18 KB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.ja.vtt 1.18 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.ja.vtt 1.18 KB
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.es-ES.vtt 1.18 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.pt-BR.vtt 1.18 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.ar.vtt 1.18 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.en.vtt 1.18 KB
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.en.vtt 1.18 KB
Part 16-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.ar.vtt 1.18 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.zh-CN.vtt 1.18 KB
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.ar.vtt 1.18 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.pt-BR.vtt 1.18 KB
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.es-ES.vtt 1.17 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.zh-CN.vtt 1.17 KB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.en.vtt 1.17 KB
Part 18-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.en.vtt 1.17 KB
Part 04-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.zh-CN.vtt 1.17 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 17 Git The Big Picture 2-rFtUkk-sCqw.pt-BR.vtt 1.17 KB
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.ar.vtt 1.17 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.zh-CN.vtt 1.17 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.en.vtt 1.17 KB
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.th.vtt 1.17 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.pt-BR.vtt 1.17 KB
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.pt-BR.vtt 1.17 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.ar.vtt 1.17 KB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.pt-BR.vtt 1.17 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.pt-BR.vtt 1.17 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/04. Ud1110 IntroPy L5 22 Continue Crawl Solution-tLhTfSZ6LRA.zh-CN.vtt 1.17 KB
Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.en.vtt 1.17 KB
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.it.vtt 1.17 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.es-ES.vtt 1.17 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.ar.vtt 1.16 KB
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.ja.vtt 1.16 KB
Part 08-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.pt-BR.vtt 1.16 KB
Part 16-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.ar.vtt 1.16 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.es-MX.vtt 1.16 KB
Part 16-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.ar.vtt 1.16 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.en.vtt 1.16 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.en-US.vtt 1.16 KB
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.th.vtt 1.16 KB
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.pt-BR.vtt 1.16 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.ar.vtt 1.16 KB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.pt-BR.vtt 1.16 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.en.vtt 1.16 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.pt-BR.vtt 1.16 KB
Part 16-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.en.vtt 1.16 KB
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.ar.vtt 1.16 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 17 Git The Big Picture 2-rFtUkk-sCqw.en.vtt 1.16 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.zh-CN.vtt 1.16 KB
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.pt-BR.vtt 1.16 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.pt-BR.vtt 1.15 KB
Part 16-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.es-MX.vtt 1.15 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.zh-CN.vtt 1.15 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 44 Bye Bye!-lRYvuMf33eY.ar.vtt 1.15 KB
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.th.vtt 1.15 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/03. Parch Posey Database-JOMI560DgXg.zh-CN.vtt 1.15 KB
Part 03-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.zh-CN.vtt 1.15 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.pt-BR.vtt 1.15 KB
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.pt-BR.vtt 1.15 KB
Part 16-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.zh-CN.vtt 1.15 KB
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.zh-CN.vtt 1.15 KB
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.ar.vtt 1.15 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.pt-BR.vtt 1.15 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/04. Entity Relationship Diagrams-YY2TAJLEINA.pt-BR.vtt 1.15 KB
Part 03-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.pt-BR.vtt 1.15 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.ja.vtt 1.15 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.ar.vtt 1.15 KB
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.en.vtt 1.15 KB
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.en.vtt 1.15 KB
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.ar.vtt 1.15 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.ar.vtt 1.15 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.ja.vtt 1.15 KB
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.ja.vtt 1.15 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/06. Projects and Progress-Z9ZLMQWsbsk.en.vtt 1.15 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/07. Projects and Progress-Z9ZLMQWsbsk.en.vtt 1.15 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.zh-CN.vtt 1.15 KB
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.ar.vtt 1.14 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.pt-BR.vtt 1.14 KB
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.zh-CN.vtt 1.14 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.zh-CN.vtt 1.14 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.zh-CN.vtt 1.14 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 25 Git Log Vs Git Log --Oneline Walkthru-rn6v_QgYFnU.en.vtt 1.14 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.pt-PT.vtt 1.14 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.ar.vtt 1.14 KB
Part 16-Module 01-Lesson 07_Regressions/37. Regression Mini-Project Video-CrD9jN3rBM8.zh-CN.vtt 1.14 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.pt-BR.vtt 1.14 KB
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.en.vtt 1.14 KB
Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.en.vtt 1.14 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.ar.vtt 1.14 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.tr.vtt 1.14 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.es-ES.vtt 1.14 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Python Documentation-lBtG0DO_KqM.pt-BR.vtt 1.14 KB
Part 04-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.zh-CN.vtt 1.14 KB
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.ar.vtt 1.14 KB
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.en.vtt 1.14 KB
Part 04-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.pt-BR.vtt 1.14 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.ar.vtt 1.14 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.ja.vtt 1.14 KB
Part 16-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.en.vtt 1.14 KB
Part 08-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.ar.vtt 1.14 KB
Part 16-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.zh-CN.vtt 1.14 KB
Part 15-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.pt-BR.vtt 1.13 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.en.vtt 1.13 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.ja.vtt 1.13 KB
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Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.ja.vtt 1.13 KB
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.ar.vtt 1.13 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.ar.vtt 1.13 KB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.ja.vtt 1.13 KB
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.ja.vtt 1.13 KB
Part 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.pt-BR.vtt 1.13 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.ja.vtt 1.13 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.ar.vtt 1.13 KB
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.ar.vtt 1.13 KB
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Part 16-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video-68EGMItJiNM.pt-BR.vtt 1.13 KB
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.en.vtt 1.13 KB
Part 04-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.pt-BR.vtt 1.13 KB
Part 16-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.ja.vtt 1.13 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.zh-CN.vtt 1.13 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.zh-CN.vtt 1.13 KB
Part 04-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.zh-CN.vtt 1.12 KB
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Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.pt-BR.vtt 1.12 KB
Part 16-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.en.vtt 1.12 KB
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Part 16-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.ja.vtt 1.12 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.en.vtt 1.12 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.pt-BR.vtt 1.12 KB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.pt-BR.vtt 1.12 KB
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Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.ar.vtt 1.12 KB
Part 08-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.zh-CN.vtt 1.12 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.pt-BR.vtt 1.12 KB
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Part 18-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.zh-CN.vtt 1.12 KB
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.ar.vtt 1.12 KB
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Part 16-Module 01-Lesson 15_Evaluation Metrics/16. Precision and Recall-3vT0kSBCLdU.en.vtt 1.12 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.pt-BR.vtt 1.12 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.en.vtt 1.12 KB
Part 03-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.pt-BR.vtt 1.11 KB
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.en.vtt 1.11 KB
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.zh-CN.vtt 1.11 KB
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Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.es-ES.vtt 1.11 KB
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Part 04-Module 01-Lesson 12_Hypothesis Testing/29. Hypothesis Testing Conclusion-nQFchD4XPPs.pt-BR.vtt 1.11 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/25. WHERE with Non-Numeric Data-_pLx7MHOyjo.en.vtt 1.11 KB
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Part 03-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.en.vtt 1.11 KB
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.ja.vtt 1.11 KB
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Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.pt-BR.vtt 1.11 KB
Part 07-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.zh-CN.vtt 1.11 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.es-ES.vtt 1.11 KB
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.ar.vtt 1.1 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.zh-CN.vtt 1.1 KB
Part 16-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.zh-CN.vtt 1.1 KB
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.ar.vtt 1.1 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.en.vtt 1.1 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.zh-CN.vtt 1.1 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 37 Squashing Bugs-X-GqfxYpaw0.en.vtt 1.1 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.en.vtt 1.1 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.ja.vtt 1.1 KB
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/01. Introduction-2Y279421n3A.ar.vtt 1.1 KB
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/18. Ud1110 IntroPy L250 End Of Lesson 2-UhvyD_60esQ.ar.vtt 1.1 KB
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.ar.vtt 1.1 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.en.vtt 1.1 KB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.ja.vtt 1.1 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 37 Squashing Bugs-X-GqfxYpaw0.pt-BR.vtt 1.1 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Python Documentation-lBtG0DO_KqM.zh-CN.vtt 1.1 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.pt-BR.vtt 1.1 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/08. How Does Project Submission Work-jCJa_VP6qgg.en.vtt 1.1 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/09. How Does Project Submission Work-jCJa_VP6qgg.en.vtt 1.1 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/07. Outro-ot4fPX1jzOI.zh-CN.vtt 1.1 KB
Part 08-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.pt-BR.vtt 1.1 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Instructor Introduction Charlie And Phillip-8ar0mETDrZw.pt-BR.vtt 1.1 KB
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.en.vtt 1.1 KB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.ja.vtt 1.1 KB
Part 08-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.zh-CN.vtt 1.1 KB
Part 18-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.zh-CN.vtt 1.1 KB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.pt-BR.vtt 1.1 KB
Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.ja.vtt 1.1 KB
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.pt-BR.vtt 1.09 KB
Part 15-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.zh-CN.vtt 1.09 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.es-ES.vtt 1.09 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.ar.vtt 1.09 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.pt-BR.vtt 1.09 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.pt-BR.vtt 1.09 KB
Part 16-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.zh-CN.vtt 1.09 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.en.vtt 1.09 KB
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.ar.vtt 1.09 KB
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.zh-CN.vtt 1.09 KB
Part 16-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.zh-CN.vtt 1.09 KB
Part 15-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.zh-CN.vtt 1.09 KB
Part 08-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.zh-CN.vtt 1.09 KB
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.en.vtt 1.09 KB
Part 04-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.pt-BR.vtt 1.09 KB
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.ar.vtt 1.09 KB
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.en.vtt 1.09 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.pt-BR.vtt 1.09 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.en.vtt 1.09 KB
Part 07-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.zh-CN.vtt 1.09 KB
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.th.vtt 1.09 KB
Part 18-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.en.vtt 1.09 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.zh-CN.vtt 1.09 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.en.vtt 1.09 KB
Part 03-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.ar.vtt 1.09 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.zh-CN.vtt 1.09 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.ar.vtt 1.09 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.ja.vtt 1.09 KB
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.ja.vtt 1.09 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.ja.vtt 1.09 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.zh-Hans.vtt 1.09 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.pt-BR.vtt 1.08 KB
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.ar.vtt 1.08 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.it.vtt 1.08 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.ja.vtt 1.08 KB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.en.vtt 1.08 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.en-US.vtt 1.08 KB
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.th.vtt 1.08 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.en.vtt 1.08 KB
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/07. Outro-ot4fPX1jzOI.pt-BR.vtt 1.08 KB
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.zh-CN.vtt 1.08 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.en.vtt 1.08 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.en.vtt 1.08 KB
Part 18-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.zh-CN.vtt 1.08 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.ja.vtt 1.08 KB
Part 16-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.zh-CN.vtt 1.08 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.zh-CN.vtt 1.08 KB
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.zh-CN.vtt 1.08 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.en.vtt 1.08 KB
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.zh-CN.vtt 1.08 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.en.vtt 1.08 KB
Part 16-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.pt-BR.vtt 1.08 KB
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.ja.vtt 1.08 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.ar.vtt 1.08 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.zh-CN.vtt 1.08 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-hW_1ASU-j8A.ar.vtt 1.07 KB
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.ar.vtt 1.07 KB
Part 16-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.ja.vtt 1.07 KB
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.pt-BR.vtt 1.07 KB
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.ar.vtt 1.07 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 33 Git Log Vs Git Log --Stat Walkthru-aOICKP_9xiY.pt-BR.vtt 1.07 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.zh-CN.vtt 1.07 KB
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.pt-BR.vtt 1.07 KB
Part 15-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.zh-CN.vtt 1.07 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/13. How Do We Choose Between Hypotheses-JkXTwS-5Daw.en.vtt 1.07 KB
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.ar.vtt 1.07 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.en.vtt 1.07 KB
Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.pt-BR.vtt 1.07 KB
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.pt-BR.vtt 1.07 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.pt-BR.vtt 1.07 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.ar.vtt 1.07 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.pt-BR.vtt 1.07 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.ar.vtt 1.07 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.es-ES.vtt 1.07 KB
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.en.vtt 1.07 KB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.en.vtt 1.07 KB
Part 18-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.pt-BR.vtt 1.07 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.ar.vtt 1.07 KB
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/08. Ud1110 IntroPy L5 37 Squashing Bugs-X-GqfxYpaw0.zh-CN.vtt 1.07 KB
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.zh-CN.vtt 1.07 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.zh-CN.vtt 1.06 KB
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.zh-CN.vtt 1.06 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.ja.vtt 1.06 KB
Part 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.en-US.vtt 1.06 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/24. Final Thoughts-CNGDocH1k3k.ja.vtt 1.06 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/29. Hypothesis Testing Conclusion-nQFchD4XPPs.en.vtt 1.06 KB
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.ja.vtt 1.06 KB
Part 11-Module 01-Lesson 01_What is Version Control/06. Onward-iXbMaTwfIJI.en.vtt 1.06 KB
Part 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.en.vtt 1.06 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.ar.vtt 1.06 KB
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.ar.vtt 1.06 KB
Part 11-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 17 Git The Big Picture 2-rFtUkk-sCqw.zh-CN.vtt 1.06 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.ja.vtt 1.06 KB
Part 04-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.zh-CN.vtt 1.06 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.en-US.vtt 1.06 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.en.vtt 1.06 KB
Part 15-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.pt-BR.vtt 1.06 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.pt-BR.vtt 1.06 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/07. A Repository's History - Outro-9rUf2HbdAd8.pt-BR.vtt 1.06 KB
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.en.vtt 1.06 KB
Part 04-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.en.vtt 1.06 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.en.vtt 1.06 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-hW_1ASU-j8A.ja.vtt 1.06 KB
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.ar.vtt 1.06 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.zh-CN.vtt 1.06 KB
Part 15-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.en.vtt 1.06 KB
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.ar.vtt 1.06 KB
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.pt-BR.vtt 1.06 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.zh-CN.vtt 1.05 KB
Part 16-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.en.vtt 1.05 KB
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.ar.vtt 1.05 KB
Part 15-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.en-US.vtt 1.05 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.zh-CN.vtt 1.05 KB
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.ja.vtt 1.05 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.en.vtt 1.05 KB
Part 03-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.ar.vtt 1.05 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.ar.vtt 1.05 KB
Part 15-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.en.vtt 1.05 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.hr.vtt 1.05 KB
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.zh-CN.vtt 1.05 KB
Part 15-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.en.vtt 1.05 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.zh-CN.vtt 1.05 KB
Part 03-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.en.vtt 1.05 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/04. Entity Relationship Diagrams-YY2TAJLEINA.en.vtt 1.05 KB
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.ar.vtt 1.05 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.ar.vtt 1.05 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/08. How Does Project Submission Work-jCJa_VP6qgg.pt-BR.vtt 1.05 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/09. How Does Project Submission Work-jCJa_VP6qgg.pt-BR.vtt 1.05 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.pt-BR.vtt 1.05 KB
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.ar.vtt 1.05 KB
Part 16-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.zh-CN.vtt 1.05 KB
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.pt-BR.vtt 1.05 KB
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.ar.vtt 1.05 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/07. Projects and Progress-Z9ZLMQWsbsk.zh-CN.vtt 1.05 KB
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.pt-BR.vtt 1.05 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/06. Projects and Progress-Z9ZLMQWsbsk.zh-CN.vtt 1.05 KB
Part 02-Module 01-Lesson 04_Files and Modules/10. Ud1110 IntroPy L4 99 Lesson Outro-8AOietAcOLk.pt-BR.vtt 1.05 KB
Part 08-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.zh-CN.vtt 1.05 KB
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.pt-BR.vtt 1.05 KB
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.en.vtt 1.05 KB
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.ar.vtt 1.05 KB
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.pt-BR.vtt 1.05 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.ar.vtt 1.05 KB
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.ja.vtt 1.05 KB
Part 08-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.zh-CN.vtt 1.04 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.ar.vtt 1.04 KB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.zh-CN.vtt 1.04 KB
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/01. Intro Project Explore Weather Trends-xneztkf0TsY.en.vtt 1.04 KB
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.pt-BR.vtt 1.04 KB
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.en.vtt 1.04 KB
Part 08-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.en.vtt 1.04 KB
Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.en.vtt 1.04 KB
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.ar.vtt 1.04 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.en.vtt 1.04 KB
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-r5qca6q4Fn4.ar.vtt 1.04 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.zh-CN.vtt 1.04 KB
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.th.vtt 1.04 KB
Part 07-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.ja.vtt 1.04 KB
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Ud1110 IntroPy L1 53 Lesson 1 Done!-y3dstGZWPgc.ar.vtt 1.04 KB
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.pt-BR.vtt 1.04 KB
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.en.vtt 1.04 KB
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.ar.vtt 1.04 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.en.vtt 1.04 KB
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.en.vtt 1.04 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.pt-BR.vtt 1.04 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.ar.vtt 1.04 KB
Part 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.zh-CN.vtt 1.04 KB
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.zh-CN.vtt 1.04 KB
Part 15-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.pt-BR.vtt 1.03 KB
Part 06-Module 01-Lesson 01_Welcome to Term 2!/09. How Does Project Submission Work-jCJa_VP6qgg.zh-CN.vtt 1.03 KB
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/08. How Does Project Submission Work-jCJa_VP6qgg.zh-CN.vtt 1.03 KB
Part 08-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.en.vtt 1.03 KB
Part 16-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video-68EGMItJiNM.en.vtt 1.03 KB
Part 16-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.ar.vtt 1.03 KB
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.ja.vtt 1.03 KB
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.zh-CN.vtt 1.03 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.en.vtt 1.03 KB
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.en.vtt 1.03 KB
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.ar.vtt 1.03 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.zh-CN.vtt 1.03 KB
Part 04-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.zh-CN.vtt 1.03 KB
Part 15-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.pt-BR.vtt 1.03 KB
Part 04-Module 01-Lesson 12_Hypothesis Testing/13. How Do We Choose Between Hypotheses-JkXTwS-5Daw.pt-BR.vtt 1.03 KB
Part 16-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.pt-BR.vtt 1.03 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 25 Git Log Vs Git Log --Oneline Walkthru-rn6v_QgYFnU.zh-CN.vtt 1.03 KB
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.en-US.vtt 1.03 KB
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.pt-BR.vtt 1.03 KB
Part 15-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.en-US.vtt 1.03 KB
Part 07-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.zh-CN.vtt 1.03 KB
Part 16-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.ar.vtt 1.03 KB
Part 16-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.zh-CN.vtt 1.03 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.pt-BR.vtt 1.03 KB
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.zh-CN.vtt 1.03 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.ja.vtt 1.02 KB
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.ar.vtt 1.02 KB
Part 15-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.en.vtt 1.02 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.zh-CN.vtt 1.02 KB
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.ar.vtt 1.02 KB
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.en.vtt 1.02 KB
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.en.vtt 1.02 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.pt-BR.vtt 1.02 KB
Part 16-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.en.vtt 1.02 KB
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.en.vtt 1.02 KB
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.en.vtt 1.02 KB
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.ar.vtt 1.02 KB
Part 18-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.ar.vtt 1.02 KB
Part 15-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.zh-CN.vtt 1.02 KB
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.en.vtt 1.02 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.en.vtt 1.02 KB
Part 16-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.pt-BR.vtt 1.02 KB
Part 16-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.en.vtt 1.02 KB
Part 15-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.es-MX.vtt 1.02 KB
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.zh-CN.vtt 1.02 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.pt-BR.vtt 1.02 KB
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.pt-BR.vtt 1.02 KB
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.pt-BR.vtt 1.02 KB
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.pt-BR.vtt 1.02 KB
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.ar.vtt 1.02 KB
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-Och80L_uNjU.ar.vtt 1.02 KB
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.zh-CN.vtt 1.01 KB
Part 04-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.zh-CN.vtt 1.01 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/07. A Repository's History - Outro-9rUf2HbdAd8.en.vtt 1.01 KB
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.en.vtt 1.01 KB
Part 16-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.ar.vtt 1.01 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.en.vtt 1.01 KB
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.pt-BR.vtt 1.01 KB
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.ar.vtt 1.01 KB
Part 15-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.zh-CN.vtt 1.01 KB
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.ar.vtt 1.01 KB
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.ar.vtt 1.01 KB
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.pt-BR.vtt 1.01 KB
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.ar.vtt 1.01 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.ja.vtt 1.01 KB
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.en.vtt 1.01 KB
Part 08-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.ar.vtt 1.01 KB
Part 16-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.en.vtt 1.01 KB
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.pt-BR.vtt 1.01 KB
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.ar.vtt 1.01 KB
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.ar.vtt 1 KB
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.zh-CN.vtt 1 KB
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.ja.vtt 1 KB
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.ar.vtt 1 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.zh-CN.vtt 1 KB
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.ar.vtt 1 KB
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.zh-CN.vtt 1 KB
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.pt-BR.vtt 1 KB
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.zh-CN.vtt 1 KB
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.pt-BR.vtt 1 KB
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.th.vtt 1 KB
Part 11-Module 01-Lesson 03_Review a Repo's History/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 33 Git Log Vs Git Log --Stat Walkthru-aOICKP_9xiY.en.vtt 1023 B
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.zh-CN.vtt 1022 B
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.en.vtt 1021 B
Part 18-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.pt-BR.vtt 1021 B
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.th.vtt 1021 B
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.en.vtt 1020 B
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.pt-BR.vtt 1019 B
Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.ar.vtt 1019 B
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.ja.vtt 1018 B
Part 15-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.zh-CN.vtt 1018 B
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.pt-BR.vtt 1018 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.en.vtt 1017 B
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.pt-BR.vtt 1017 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/24. Final Thoughts-CNGDocH1k3k.pt-BR.vtt 1017 B
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.ar.vtt 1016 B
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.ar.vtt 1016 B
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.pt-BR.vtt 1016 B
Part 03-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.zh-CN.vtt 1015 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.th.vtt 1015 B
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.en.vtt 1015 B
Part 04-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.zh-CN.vtt 1014 B
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.pt-BR.vtt 1014 B
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.zh-CN.vtt 1014 B
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.pt-BR.vtt 1014 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.en.vtt 1013 B
Part 16-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.zh-CN.vtt 1012 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.pt-BR.vtt 1012 B
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.zh-CN.vtt 1012 B
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.zh-CN.vtt 1012 B
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.en.vtt 1012 B
Part 15-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.pt-BR.vtt 1011 B
Part 02-Module 01-Lesson 04_Files and Modules/10. Ud1110 IntroPy L4 99 Lesson Outro-8AOietAcOLk.en.vtt 1011 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.it.vtt 1010 B
Part 16-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.zh-CN.vtt 1010 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/19. Congratulations!-_FPpbuuW-1o.ar.vtt 1009 B
Part 08-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.en.vtt 1008 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.ar.vtt 1008 B
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.ar.vtt 1008 B
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.en.vtt 1008 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.en.vtt 1008 B
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.en-US.vtt 1007 B
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.pt-BR.vtt 1007 B
Part 18-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.zh-CN.vtt 1007 B
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.ar.vtt 1006 B
Part 07-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.pt-BR.vtt 1006 B
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.ja.vtt 1005 B
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.en.vtt 1005 B
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.zh-CN.vtt 1004 B
Part 03-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.zh-CN.vtt 1004 B
Part 02-Module 01-Lesson 01_Numbers and Strings/01. Instructor Introduction Charlie And Phillip-8ar0mETDrZw.en.vtt 1004 B
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.zh-CN.vtt 1004 B
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.en.vtt 1004 B
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/25. WHERE with Non-Numeric Data-_pLx7MHOyjo.zh-CN.vtt 1004 B
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.pt-BR.vtt 1004 B
Part 16-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.zh-CN.vtt 1003 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.es-ES.vtt 1003 B
Part 03-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.zh-CN.vtt 1003 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.ar.vtt 1002 B
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.pt-BR.vtt 1002 B
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.pt-BR.vtt 1002 B
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.en.vtt 1001 B
Part 07-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.pt-BR.vtt 1001 B
Part 16-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.ja.vtt 1001 B
Part 16-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.zh-CN.vtt 1001 B
Part 16-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.en.vtt 1000 B
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.ja.vtt 1000 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.ar.vtt 1000 B
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.ar.vtt 999 B
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.ar.vtt 999 B
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.ja.vtt 999 B
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.zh-CN.vtt 999 B
Part 16-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.ar.vtt 998 B
Part 16-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.zh-CN.vtt 998 B
Part 11-Module 01-Lesson 06_Undoing Changes/06. Course Outro-twn_cheqoK8.en.vtt 998 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.en.vtt 997 B
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.pt-BR.vtt 996 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/16. Precision and Recall-3vT0kSBCLdU.zh-CN.vtt 996 B
Part 04-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.zh-CN.vtt 996 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.it.vtt 994 B
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.zh-CN.vtt 994 B
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.ja.vtt 993 B
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.pt-BR.vtt 993 B
Part 15-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.pt-BR.vtt 993 B
Part 16-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.zh-CN.vtt 993 B
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.en.vtt 993 B
Part 16-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.ar.vtt 991 B
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.pt-BR.vtt 991 B
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.en.vtt 991 B
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.pt-BR.vtt 989 B
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.pt-BR.vtt 989 B
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.ja.vtt 989 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.en.vtt 988 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.pt-BR.vtt 988 B
Part 04-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.zh-CN.vtt 987 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.pt-BR.vtt 987 B
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.en.vtt 986 B
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.pt-BR.vtt 984 B
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.en.vtt 984 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.ja.vtt 984 B
Part 04-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.pt-BR.vtt 983 B
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.ja.vtt 983 B
Part 16-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.pt-BR.vtt 983 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.ar.vtt 982 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.zh-CN.vtt 982 B
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.zh-CN.vtt 980 B
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.pt-BR.vtt 980 B
Part 03-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.zh-CN.vtt 979 B
Part 08-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.zh-CN.vtt 979 B
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/04. Entity Relationship Diagrams-YY2TAJLEINA.zh-CN.vtt 979 B
Part 04-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.en.vtt 979 B
Part 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.zh-CN.vtt 978 B
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.pt-BR.vtt 977 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.en.vtt 976 B
Part 16-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.ar.vtt 976 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.zh-CN.vtt 976 B
Part 16-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.zh-CN.vtt 976 B
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.es-MX.vtt 975 B
Part 07-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.zh-CN.vtt 975 B
Part 07-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.zh-CN.vtt 975 B
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.pt-BR.vtt 975 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.es-ES.vtt 975 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.ar.vtt 975 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.pt-BR.vtt 974 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.ar.vtt 974 B
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.ja.vtt 973 B
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.en.vtt 973 B
Part 11-Module 01-Lesson 01_What is Version Control/06. Onward-iXbMaTwfIJI.zh-CN.vtt 973 B
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.ar.vtt 973 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.pt-BR.vtt 972 B
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.ja.vtt 971 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.es-ES.vtt 971 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.th.vtt 970 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.pt-BR.vtt 970 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.en.vtt 969 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.pt-BR.vtt 969 B
Part 07-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.zh-CN.vtt 969 B
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.ar.vtt 969 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.it.vtt 969 B
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.ar.vtt 967 B
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.ar.vtt 967 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.it.vtt 967 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.es-ES.vtt 967 B
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages/01. Intro Project Explore Weather Trends-xneztkf0TsY.zh-CN.vtt 966 B
Part 15-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.pt-BR.vtt 966 B
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.ja.vtt 966 B
Part 16-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.en.vtt 966 B
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.zh-CN.vtt 966 B
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.ja.vtt 966 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/24. Final Thoughts-CNGDocH1k3k.en.vtt 965 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.pt-BR.vtt 965 B
Part 16-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.ar.vtt 965 B
Part 15-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.zh-CN.vtt 965 B
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.en.vtt 964 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.en.vtt 964 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.zh-CN.vtt 964 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.zh-CN.vtt 964 B
Part 07-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.ar.vtt 964 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.en.vtt 963 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.ar.vtt 963 B
Part 08-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.pt-BR.vtt 963 B
Part 16-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.zh-CN.vtt 962 B
Part 04-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.pt-BR.vtt 962 B
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.zh-CN.vtt 962 B
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.pt-BR.vtt 962 B
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.en-US.vtt 960 B
Part 16-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.pt-BR.vtt 960 B
Part 11-Module 01-Lesson 02_Create A Git Repo/05. Create A Repo - Outro-h7j4STDFCjs.ar.vtt 959 B
Part 12-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.pt-BR.vtt 959 B
Part 04-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.en.vtt 959 B
Part 02-Module 01-Lesson 03_Data Structures and Loops/01. Ud1110 IntroPy L301 Welcome To Lesson 3-ikOWhrOUgLc.ar.vtt 958 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.en.vtt 958 B
Part 16-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.en.vtt 958 B
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.en.vtt 957 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.hr.vtt 957 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.es-ES.vtt 957 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.ja.vtt 957 B
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.pt-BR.vtt 957 B
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.en.vtt 956 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.hr.vtt 956 B
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.pt-BR.vtt 956 B
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.pt-BR.vtt 954 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.pt-BR.vtt 953 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.en.vtt 953 B
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.ja.vtt 953 B
Part 16-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.zh-CN.vtt 953 B
Part 18-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.ar.vtt 953 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.en.vtt 952 B
Part 16-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.ja.vtt 952 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.ja.vtt 952 B
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 44 Bye Bye!-lRYvuMf33eY.pt-BR.vtt 951 B
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.en.vtt 951 B
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.en.vtt 951 B
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.ja.vtt 950 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.pt-BR.vtt 950 B
Part 15-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.pt-BR.vtt 950 B
Part 04-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.zh-CN.vtt 949 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.ja.vtt 949 B
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.ar.vtt 948 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.es-ES.vtt 948 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.es-ES.vtt 948 B
Part 11-Module 01-Lesson 03_Review a Repo's History/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 33 Git Log Vs Git Log --Stat Walkthru-aOICKP_9xiY.zh-CN.vtt 948 B
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.ja.vtt 947 B
Part 07-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.zh-CN.vtt 947 B
Part 07-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.ar.vtt 946 B
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.en.vtt 945 B
Part 08-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.ar.vtt 945 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.it.vtt 945 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.zh-CN.vtt 944 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.pt-BR.vtt 944 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.pt-BR.vtt 944 B
Part 18-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.en.vtt 944 B
Part 07-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.zh-CN.vtt 943 B
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.en.vtt 943 B
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.en-US.vtt 942 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.hr.vtt 942 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 2-so5zydnbYEg.ar.vtt 942 B
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.zh-CN.vtt 942 B
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.en.vtt 942 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.ar.vtt 941 B
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.ja.vtt 940 B
Part 07-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.zh-CN.vtt 940 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.en.vtt 940 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.en.vtt 940 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 3-oVGmi4zBOT8.en.vtt 940 B
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.en.vtt 939 B
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.en.vtt 939 B
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.ar.vtt 938 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.pt-BR.vtt 937 B
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.pt-BR.vtt 937 B
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.en.vtt 937 B
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.pt-BR.vtt 937 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.pt-BR.vtt 937 B
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.en.vtt 936 B
Part 08-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.zh-CN.vtt 935 B
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.zh-CN.vtt 935 B
Part 04-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.pt-BR.vtt 935 B
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.en.vtt 935 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.pt-BR.vtt 935 B
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.zh-CN.vtt 935 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.zh-CN.vtt 935 B
Part 16-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.ja.vtt 935 B
Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.ar.vtt 934 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.pt-BR.vtt 933 B
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.ja.vtt 933 B
Part 11-Module 01-Lesson 03_Review a Repo's History/07. A Repository's History - Outro-9rUf2HbdAd8.zh-CN.vtt 933 B
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.en.vtt 933 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-hW_1ASU-j8A.pt-BR.vtt 932 B
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.en.vtt 931 B
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.zh-CN.vtt 931 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.en.vtt 931 B
Part 04-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.zh-CN.vtt 930 B
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.pt-BR.vtt 930 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.pt-BR.vtt 930 B
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.ar.vtt 930 B
Part 11-Module 01-Lesson 06_Undoing Changes/06. Course Outro-twn_cheqoK8.zh-CN.vtt 928 B
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.ar.vtt 928 B
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.en.vtt 928 B
Part 16-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.pt-BR.vtt 928 B
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.pt-BR.vtt 928 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.zh-CN.vtt 927 B
Part 15-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.zh-CN.vtt 927 B
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.ja.vtt 927 B
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.en.vtt 927 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.ar.vtt 926 B
Part 16-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.pt-BR.vtt 926 B
Part 07-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.ar.vtt 926 B
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.pt-BR.vtt 925 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.hr.vtt 925 B
Part 08-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.zh-CN.vtt 925 B
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.en.vtt 924 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.ar.vtt 924 B
Part 16-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.zh-CN.vtt 924 B
Part 07-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.en.vtt 924 B
Part 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.zh-CN.vtt 924 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.ja.vtt 923 B
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.en.vtt 923 B
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.pt-BR.vtt 921 B
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-r5qca6q4Fn4.ja.vtt 921 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.ar.vtt 920 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-hW_1ASU-j8A.en.vtt 920 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.pt-BR.vtt 919 B
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.ja.vtt 919 B
Part 07-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.en.vtt 919 B
Part 02-Module 01-Lesson 04_Files and Modules/10. Ud1110 IntroPy L4 99 Lesson Outro-8AOietAcOLk.zh-CN.vtt 918 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 3-oVGmi4zBOT8.pt-BR.vtt 917 B
Part 16-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.ja.vtt 917 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.ar.vtt 916 B
Part 16-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.zh-CN.vtt 916 B
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.ar.vtt 916 B
Part 16-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.pt-BR.vtt 916 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.it.vtt 915 B
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.en.vtt 914 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.pt-BR.vtt 914 B
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.pt-BR.vtt 914 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.zh-CN.vtt 914 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.zh-CN.vtt 913 B
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.pt-BR.vtt 913 B
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.ja.vtt 913 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.zh-CN.vtt 913 B
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.en-US.vtt 913 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.zh-CN.vtt 912 B
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.ar.vtt 912 B
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.ja.vtt 912 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.ja.vtt 911 B
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.th.vtt 910 B
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.en.vtt 909 B
Part 04-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.zh-CN.vtt 908 B
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.ja.vtt 908 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.en.vtt 908 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.en.vtt 906 B
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.zh-CN.vtt 906 B
Part 04-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.en.vtt 906 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.zh-CN.vtt 905 B
Part 11-Module 01-Lesson 06_Undoing Changes/05. Undoing Changes--_PPVk2UZMU.ar.vtt 904 B
Part 16-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.zh-CN.vtt 904 B
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.pt-BR.vtt 904 B
Part 16-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.pt-BR.vtt 903 B
Part 16-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.pt-BR.vtt 903 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.ar.vtt 903 B
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.ja.vtt 902 B
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.pt-BR.vtt 902 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.ar.vtt 902 B
Part 16-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.zh-CN.vtt 902 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.pt-BR.vtt 901 B
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.ja.vtt 901 B
Part 15-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.en-US.vtt 900 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.ar.vtt 900 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.en.vtt 900 B
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.ar.vtt 900 B
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.pt-BR.vtt 900 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.es-ES.vtt 900 B
Part 15-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.zh-CN.vtt 900 B
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.en.vtt 900 B
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.ja.vtt 899 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.zh-CN.vtt 899 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.pt-BR.vtt 899 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.ar.vtt 899 B
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.en.vtt 898 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.zh-CN.vtt 898 B
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.en.vtt 898 B
Part 07-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.zh-CN.vtt 898 B
Part 15-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.en.vtt 897 B
Part 16-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.pt-BR.vtt 897 B
Part 16-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.en.vtt 897 B
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.ar.vtt 896 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.zh-CN.vtt 896 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.pt-BR.vtt 896 B
Part 11-Module 01-Lesson 06_Undoing Changes/06. Course Outro-twn_cheqoK8.pt-BR.vtt 896 B
Part 16-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.en.vtt 896 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.en-US.vtt 895 B
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.en.vtt 895 B
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.pt-BR.vtt 895 B
Part 15-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.pt-BR.vtt 895 B
Part 04-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.ar.vtt 894 B
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.ar.vtt 893 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.en.vtt 893 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.zh-CN.vtt 893 B
Part 16-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.en.vtt 893 B
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.pt-BR.vtt 893 B
Part 16-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.pt-BR.vtt 893 B
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.pt-BR.vtt 892 B
Part 04-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.zh-CN.vtt 892 B
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 44 Bye Bye!-lRYvuMf33eY.en.vtt 892 B
Part 08-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.en.vtt 891 B
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.pt-BR.vtt 891 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/24. Final Thoughts-CNGDocH1k3k.zh-CN.vtt 891 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.en.vtt 891 B
Part 04-Module 01-Lesson 12_Hypothesis Testing/29. Hypothesis Testing Conclusion-nQFchD4XPPs.zh-CN.vtt 890 B
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.pt-BR.vtt 890 B
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.pt-BR.vtt 889 B
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.zh-CN.vtt 888 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.zh-CN.vtt 888 B
Part 07-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.zh-CN.vtt 888 B
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.ar.vtt 888 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.ja.vtt 887 B
Part 04-Module 01-Lesson 12_Hypothesis Testing/13. How Do We Choose Between Hypotheses-JkXTwS-5Daw.zh-CN.vtt 887 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.es-ES.vtt 886 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.zh-CN.vtt 886 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.ar.vtt 886 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.es-ES.vtt 885 B
Part 18-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.ar.vtt 885 B
Part 04-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.en.vtt 884 B
Part 16-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.zh-CN.vtt 884 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.pt-BR.vtt 884 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.en.vtt 883 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.zh-CN.vtt 883 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.en.vtt 883 B
Part 16-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.ar.vtt 882 B
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.zh-CN.vtt 881 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.es-ES.vtt 880 B
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.pt-BR.vtt 880 B
Part 16-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.zh-CN.vtt 880 B
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.en.vtt 879 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.en.vtt 879 B
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.zh-CN.vtt 879 B
Part 16-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.en.vtt 879 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.en.vtt 879 B
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.pt-BR.vtt 879 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/01. Introduction-2Y279421n3A.pt-BR.vtt 879 B
Part 08-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.zh-CN.vtt 878 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.en.vtt 878 B
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.pt-BR.vtt 876 B
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.zh-CN.vtt 876 B
Part 07-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.zh-CN.vtt 876 B
Part 07-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.ja.vtt 876 B
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.en.vtt 876 B
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.en.vtt 875 B
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.ja.vtt 874 B
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.ja.vtt 874 B
Part 07-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.ja.vtt 874 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.en.vtt 874 B
Part 16-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.ar.vtt 874 B
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.en.vtt 874 B
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.pt-BR.vtt 873 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.ja.vtt 872 B
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.pt-BR.vtt 872 B
Part 16-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.ar.vtt 872 B
Part 16-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.en.vtt 871 B
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.ja.vtt 871 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.es-ES.vtt 870 B
Part 16-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.zh-CN.vtt 870 B
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.zh-CN.vtt 870 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.ar.vtt 869 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 3-oVGmi4zBOT8.zh-CN.vtt 869 B
Part 16-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.pt-BR.vtt 869 B
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.en.vtt 868 B
Part 16-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.ar.vtt 868 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.en-GB.vtt 868 B
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.pt-BR.vtt 867 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.pt-BR.vtt 867 B
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.pt-BR.vtt 867 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.pt-BR.vtt 866 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.it.vtt 866 B
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.ar.vtt 865 B
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.en.vtt 865 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.pt-BR.vtt 864 B
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.ar.vtt 864 B
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.pt-BR.vtt 863 B
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.ar.vtt 863 B
Part 07-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.zh-CN.vtt 863 B
Part 16-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.zh-CN.vtt 862 B
Part 16-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.zh-CN.vtt 862 B
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.pt-BR.vtt 862 B
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.zh-CN.vtt 862 B
Part 18-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.zh-CN.vtt 862 B
Part 16-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.en.vtt 861 B
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.pt-BR.vtt 861 B
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.ar.vtt 861 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.ar.vtt 861 B
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.pt-BR.vtt 861 B
Part 07-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.zh-CN.vtt 860 B
Part 16-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.zh-CN.vtt 859 B
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.zh-CN.vtt 858 B
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.pt-BR.vtt 857 B
Part 07-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.zh-CN.vtt 857 B
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-r5qca6q4Fn4.en.vtt 857 B
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.en.vtt 857 B
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.pt-BR.vtt 856 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.en.vtt 856 B
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.pt-BR.vtt 856 B
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.en.vtt 855 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.pt-BR.vtt 855 B
Part 07-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.zh-CN.vtt 855 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.hr.vtt 854 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.zh-CN.vtt 854 B
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.ar.vtt 854 B
Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.pt-BR.vtt 853 B
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.ja.vtt 853 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.zh-CN.vtt 852 B
Part 04-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.ar.vtt 851 B
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.ja.vtt 851 B
Part 16-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.pt-BR.vtt 850 B
Part 16-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.zh-CN.vtt 850 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.ar.vtt 850 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.es-ES.vtt 850 B
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.ar.vtt 850 B
Part 08-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.en.vtt 849 B
Part 15-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.zh-CN.vtt 849 B
Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.pt-BR.vtt 849 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.pt-BR.vtt 848 B
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.zh-CN.vtt 848 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.ja.vtt 847 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.ar.vtt 847 B
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.en.vtt 847 B
Part 03-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.pt-BR.vtt 847 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.zh-CN.vtt 847 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.ja.vtt 846 B
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.ar.vtt 846 B
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.en.vtt 846 B
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.ja.vtt 845 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.ar.vtt 845 B
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-r5qca6q4Fn4.pt-BR.vtt 845 B
Part 16-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.zh-CN.vtt 845 B
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.es-ES.vtt 845 B
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.ar.vtt 844 B
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.en.vtt 843 B
Part 16-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.zh-CN.vtt 842 B
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.zh-CN.vtt 842 B
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.ar.vtt 842 B
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.ja.vtt 842 B
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.ar.vtt 841 B
Part 04-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.ja.vtt 841 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.en.vtt 840 B
Part 16-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.pt-BR.vtt 840 B
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.pt-BR.vtt 839 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.en.vtt 839 B
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.zh-CN.vtt 839 B
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.ar.vtt 838 B
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.ar.vtt 838 B
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.es-ES.vtt 837 B
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 54 Content On Different Branches-Px6EUylw8Uw.ar.vtt 837 B
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/18. Ud1110 IntroPy L250 End Of Lesson 2-UhvyD_60esQ.pt-BR.vtt 837 B
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.en.vtt 837 B
Part 16-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.en.vtt 837 B
Part 16-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.zh-CN.vtt 837 B
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.it.vtt 837 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/01. Introduction-2Y279421n3A.en.vtt 836 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.en.vtt 836 B
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.ar.vtt 836 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.ja.vtt 835 B
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.ar.vtt 835 B
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.pt-BR.vtt 834 B
Part 07-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.zh-CN.vtt 834 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.ja.vtt 834 B
Part 16-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.pt-BR.vtt 832 B
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.es-MX.vtt 832 B
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.it.vtt 832 B
Part 07-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.zh-CN.vtt 831 B
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.pt-BR.vtt 830 B
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.pt-BR.vtt 830 B
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.ja.vtt 830 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.zh-CN.vtt 830 B
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.ar.vtt 830 B
Part 07-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.zh-CN.vtt 830 B
Part 07-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.zh-CN.vtt 829 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.pt-BR.vtt 829 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.ar.vtt 829 B
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.en.vtt 828 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.en.vtt 828 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.ja.vtt 828 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.zh-CN.vtt 828 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.ar.vtt 828 B
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.pt-BR.vtt 828 B
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/11. Ud1110 IntroPy L5 44 Bye Bye!-lRYvuMf33eY.zh-CN.vtt 827 B
Part 07-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.ja.vtt 827 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.en.vtt 826 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.en.vtt 826 B
Part 16-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.pt-BR.vtt 826 B
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.en-US.vtt 825 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.pt-BR.vtt 825 B
Part 03-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.en.vtt 824 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.es-ES.vtt 823 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.ar.vtt 822 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.en.vtt 821 B
Part 16-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.en.vtt 821 B
Part 16-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.ja.vtt 820 B
Part 16-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.ar.vtt 820 B
Part 16-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.en.vtt 820 B
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.ar.vtt 819 B
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.ja.vtt 819 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.zh-CN.vtt 818 B
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.en-US.vtt 818 B
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.ja.vtt 818 B
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.zh-CN.vtt 818 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.en.vtt 818 B
Part 16-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.zh-CN.vtt 817 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.es-ES.vtt 817 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.zh-CN.vtt 817 B
Part 07-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.zh-CN.vtt 817 B
Part 15-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.pt-BR.vtt 817 B
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.en.vtt 817 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.ja.vtt 816 B
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.en.vtt 816 B
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.ar.vtt 816 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.ar.vtt 816 B
Part 16-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.ar.vtt 816 B
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.en.vtt 815 B
Part 16-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.zh-CN.vtt 814 B
Part 16-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.zh-CN.vtt 814 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-Och80L_uNjU.ja.vtt 813 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.th.vtt 813 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.ja.vtt 813 B
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.en.vtt 813 B
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.ar.vtt 812 B
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.zh-CN.vtt 812 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.zh-CN.vtt 812 B
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.zh-CN.vtt 812 B
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.zh-CN.vtt 812 B
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.ja.vtt 812 B
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.pt-BR.vtt 812 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.zh-CN.vtt 811 B
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.pt-BR.vtt 811 B
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.en.vtt 811 B
Part 18-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.pt-BR.vtt 810 B
Part 08-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.ar.vtt 810 B
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.zh-CN.vtt 810 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.pt-BR.vtt 810 B
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.en.vtt 810 B
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.en.vtt 810 B
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.pt-BR.vtt 809 B
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.en.vtt 808 B
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.en.vtt 808 B
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.zh-CN.vtt 808 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.ar.vtt 807 B
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.pt-BR.vtt 806 B
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.zh-CN.vtt 806 B
Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.ja.vtt 806 B
Part 18-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.en.vtt 806 B
Part 16-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.ar.vtt 805 B
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.ja.vtt 805 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.en-GB.vtt 804 B
Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.en.vtt 804 B
Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.en.vtt 803 B
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.en.vtt 803 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.ar.vtt 802 B
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.pt-BR.vtt 802 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/23. Predictions-hW_1ASU-j8A.zh-CN.vtt 802 B
Part 04-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.pt-BR.vtt 802 B
Part 16-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.zh-CN.vtt 801 B
Part 11-Module 01-Lesson 02_Create A Git Repo/05. Create A Repo - Outro-h7j4STDFCjs.pt-BR.vtt 800 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.ar.vtt 799 B
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.zh-CN.vtt 799 B
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ar.vtt 799 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.en.vtt 799 B
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.pt-BR.vtt 798 B
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.en.vtt 798 B
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.en.vtt 798 B
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.en.vtt 797 B
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.zh-CN.vtt 797 B
Part 16-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.pt-BR.vtt 797 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.it.vtt 797 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.pt-BR.vtt 797 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-Och80L_uNjU.pt-BR.vtt 794 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.pt-BR.vtt 794 B
Part 16-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.ar.vtt 794 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.en.vtt 793 B
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.zh-CN.vtt 793 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.ar.vtt 793 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.hr.vtt 792 B
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.en.vtt 792 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.pt-BR.vtt 792 B
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.ja.vtt 792 B
Part 16-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.zh-CN.vtt 791 B
Part 14-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.en.vtt 791 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.ar.vtt 790 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.en.vtt 790 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.en.vtt 790 B
Part 16-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.pt-BR.vtt 790 B
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.en.vtt 789 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.pt-BR.vtt 788 B
Part 04-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.ar.vtt 787 B
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/18. Ud1110 IntroPy L250 End Of Lesson 2-UhvyD_60esQ.en.vtt 787 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.zh-CN.vtt 787 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.zh-CN.vtt 787 B
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.en.vtt 787 B
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.zh-CN.vtt 785 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.zh-CN.vtt 785 B
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.zh-CN.vtt 784 B
Part 16-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.ar.vtt 784 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.pt-BR.vtt 783 B
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.ja.vtt 783 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.ar.vtt 783 B
Part 07-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.zh-CN.vtt 783 B
Part 16-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.zh-CN.vtt 783 B
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.ar.vtt 783 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.en.vtt 782 B
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.pt-BR.vtt 781 B
Part 16-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.zh-CN.vtt 781 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/19. Congratulations!-_FPpbuuW-1o.en.vtt 781 B
Part 04-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.pt-BR.vtt 780 B
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.zh-CN.vtt 780 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.zh-CN.vtt 780 B
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.zh-CN.vtt 779 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.th.vtt 779 B
Part 07-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.zh-CN.vtt 778 B
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.en.vtt 778 B
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.zh-CN.vtt 778 B
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.zh-CN.vtt 778 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.ar.vtt 777 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.th.vtt 777 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.es-ES.vtt 777 B
Part 12-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.en.vtt 777 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.zh-CN.vtt 775 B
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.en.vtt 775 B
Part 07-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.pt-BR.vtt 775 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.es-ES.vtt 775 B
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.ar.vtt 774 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.ar.vtt 774 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.pt-BR.vtt 774 B
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.en.vtt 773 B
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.ar.vtt 773 B
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.pt-BR.vtt 773 B
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.pt-BR.vtt 773 B
Part 16-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.zh-CN.vtt 773 B
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.en.vtt 772 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.th.vtt 772 B
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.pt-BR.vtt 772 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.en.vtt 772 B
Part 15-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.en-US.vtt 770 B
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.en.vtt 770 B
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.en.vtt 770 B
Part 16-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.pt-BR.vtt 770 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.ar.vtt 770 B
Part 16-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.en.vtt 770 B
Part 04-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.pt-BR.vtt 769 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.pt-BR.vtt 769 B
Part 16-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.zh-CN.vtt 769 B
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.ar.vtt 769 B
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.th.vtt 768 B
Part 12-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.ar.vtt 768 B
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.en.vtt 768 B
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.it.vtt 767 B
Part 15-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.en.vtt 767 B
Part 16-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.en.vtt 766 B
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.pt-BR.vtt 766 B
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Ud1110 IntroPy L1 53 Lesson 1 Done!-y3dstGZWPgc.en.vtt 766 B
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.ar.vtt 765 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pt-PT.vtt 765 B
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.ja.vtt 765 B
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.pt-BR.vtt 765 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.it.vtt 764 B
Part 16-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.zh-CN.vtt 764 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.en.vtt 763 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.zh-CN.vtt 763 B
Part 16-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.zh-CN.vtt 763 B
Part 18-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.en.vtt 763 B
Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.ja.vtt 763 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.ja.vtt 762 B
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.ar.vtt 761 B
Part 07-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.en-US.vtt 761 B
Part 16-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.zh-CN.vtt 761 B
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.pt-BR.vtt 761 B
Part 03-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.zh-CN.vtt 761 B
Part 14-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.pt-BR.vtt 760 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.ja.vtt 760 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.zh-CN.vtt 759 B
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.en-US.vtt 759 B
Part 07-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.en.vtt 759 B
Part 16-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.pt-BR.vtt 758 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.ja.vtt 758 B
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.en.vtt 757 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.es-ES.vtt 757 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.en.vtt 757 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.en.vtt 757 B
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.en.vtt 756 B
Part 04-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.en.vtt 756 B
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.en.vtt 756 B
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Coding inside the skeleton loop-MRPdqOwnqag.ar.vtt 755 B
Part 16-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.zh-CN.vtt 754 B
Part 04-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.en.vtt 754 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.pt-BR.vtt 753 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.pt-BR.vtt 753 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.ar.vtt 752 B
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.zh-CN.vtt 752 B
Part 04-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.zh-CN.vtt 752 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.en.vtt 752 B
Part 06-Module 01-Lesson 01_Welcome to Term 2!/06. Introduction-fxNSn63xFvA.ar.vtt 751 B
Part 16-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.en.vtt 751 B
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/05. Introduction-fxNSn63xFvA.ar.vtt 751 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.zh-CN.vtt 751 B
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.ar.vtt 751 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.zh-CN.vtt 750 B
Part 04-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.zh-CN.vtt 750 B
Part 07-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.zh-CN.vtt 750 B
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.zh-CN.vtt 749 B
Part 08-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.pt-BR.vtt 749 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.es-ES.vtt 748 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.hr.vtt 748 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.zh-CN.vtt 748 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.ja.vtt 748 B
Part 16-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.zh-CN.vtt 748 B
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.en.vtt 747 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.ar.vtt 747 B
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.pt-BR.vtt 747 B
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.zh-CN.vtt 747 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.pt-BR.vtt 747 B
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.ar.vtt 747 B
Part 07-Module 01-Lesson 01_What is EDA/07. The Growth of Televisions-r5qca6q4Fn4.zh-CN.vtt 747 B
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.pt-BR.vtt 746 B
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.es-ES.vtt 746 B
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/18. Ud1110 IntroPy L250 End Of Lesson 2-UhvyD_60esQ.zh-CN.vtt 746 B
Part 18-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.pt-BR.vtt 746 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.es-ES.vtt 746 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.pt-BR.vtt 746 B
Part 18-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.zh-CN.vtt 745 B
Part 04-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.pt-BR.vtt 745 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.zh-CN.vtt 745 B
Part 16-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.ar.vtt 745 B
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.zh-CN.vtt 744 B
Part 07-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.zh-CN.vtt 743 B
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.pt-BR.vtt 743 B
Part 08-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.en.vtt 742 B
Part 04-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.zh-CN.vtt 742 B
Part 07-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.zh-CN.vtt 742 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.it.vtt 742 B
Part 15-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.zh-CN.vtt 742 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/19. Congratulations!-_FPpbuuW-1o.zh-CN.vtt 741 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.es-ES.vtt 741 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.pt-BR.vtt 741 B
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/01. Ud1110 IntroPy L201 Welcome Back!-oCCMSsCc4Iw.ar.vtt 741 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.pt-BR.vtt 739 B
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.ar.vtt 739 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.en.vtt 738 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.ar.vtt 738 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 2-so5zydnbYEg.pt-BR.vtt 737 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.pt-BR.vtt 737 B
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.pt-BR.vtt 737 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.pt-BR.vtt 736 B
Part 04-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.zh-CN.vtt 736 B
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.pt-BR.vtt 736 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.en.vtt 736 B
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.en.vtt 736 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/01. Introduction-2Y279421n3A.zh-CN.vtt 736 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.ja.vtt 735 B
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.pt-BR.vtt 735 B
Part 04-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.pt-BR.vtt 735 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.en.vtt 734 B
Part 16-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.pt-BR.vtt 733 B
Part 16-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.zh-CN.vtt 733 B
Part 16-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.zh-CN.vtt 732 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.en.vtt 732 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.ar.vtt 731 B
Part 04-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.ar.vtt 731 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.ja.vtt 730 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.es-ES.vtt 729 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-Och80L_uNjU.en.vtt 729 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.th.vtt 729 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.es-ES.vtt 728 B
Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.pt-BR.vtt 728 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.pt-BR.vtt 728 B
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.en.vtt 728 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.en.vtt 728 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.ar.vtt 727 B
Part 16-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.ja.vtt 727 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.ar.vtt 726 B
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.ar.vtt 726 B
Part 18-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.zh-CN.vtt 724 B
Part 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.zh-CN.vtt 723 B
Part 12-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.zh-CN.vtt 723 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.th.vtt 723 B
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.en.vtt 722 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.zh-CN.vtt 722 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.ar.vtt 722 B
Part 11-Module 01-Lesson 02_Create A Git Repo/05. Create A Repo - Outro-h7j4STDFCjs.en.vtt 720 B
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.zh-CN.vtt 720 B
Part 08-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.en.vtt 719 B
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.ar.vtt 719 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.ar.vtt 717 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.ja.vtt 717 B
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.th.vtt 717 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.en.vtt 717 B
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.pt-BR.vtt 717 B
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.pt-BR.vtt 717 B
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.en.vtt 717 B
Part 16-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.pt-BR.vtt 716 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.ja.vtt 716 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.en.vtt 715 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pl.vtt 715 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.en.vtt 715 B
Part 03-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.zh-CN.vtt 715 B
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.en.vtt 714 B
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.zh-CN.vtt 713 B
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.ar.vtt 713 B
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.ar.vtt 713 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.it.vtt 712 B
Part 16-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.pt-BR.vtt 711 B
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.ar.vtt 711 B
Part 16-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.zh-CN.vtt 711 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.ja.vtt 710 B
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.en.vtt 709 B
Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.en.vtt 709 B
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.ja.vtt 708 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.zh-CN.vtt 708 B
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.ja.vtt 708 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.ja.vtt 708 B
Part 14-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.es-MX.vtt 707 B
Part 04-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.zh-CN.vtt 707 B
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.pt-BR.vtt 707 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.ar.vtt 706 B
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.pt-BR.vtt 705 B
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.en.vtt 705 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.pt-BR.vtt 705 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.zh-CN.vtt 704 B
Part 16-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.zh-CN.vtt 704 B
Part 09-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.ar.vtt 704 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.en.vtt 704 B
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.ar.vtt 703 B
Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.zh-CN.vtt 703 B
Part 08-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.zh-CN.vtt 703 B
Part 04-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.pt-BR.vtt 702 B
Part 16-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.en.vtt 702 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.it.vtt 702 B
Part 07-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.ja.vtt 701 B
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.pt-BR.vtt 701 B
Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.zh-CN.vtt 701 B
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.pt-BR.vtt 701 B
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.zh-CN.vtt 701 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.zh-CN.vtt 701 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.pt-BR.vtt 700 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.th.vtt 700 B
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.en.vtt 699 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.pt-BR.vtt 699 B
Part 07-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.pt-BR.vtt 698 B
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.zh-CN.vtt 698 B
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.zh-CN.vtt 698 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.zh-CN.vtt 698 B
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.it.vtt 697 B
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.ar.vtt 697 B
Part 16-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.pt-BR.vtt 697 B
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.pt-BR.vtt 696 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.pt-BR.vtt 696 B
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.pt-BR.vtt 696 B
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.pt-BR.vtt 695 B
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.pt-BR.vtt 695 B
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.it.vtt 695 B
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.ar.vtt 694 B
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.zh-CN.vtt 694 B
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.pt-BR.vtt 694 B
Part 08-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.pt-BR.vtt 693 B
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Ud1110 IntroPy L1 53 Lesson 1 Done!-y3dstGZWPgc.pt-BR.vtt 693 B
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.ar.vtt 693 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.pt-BR.vtt 692 B
Part 07-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.zh-CN.vtt 692 B
Part 04-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.pt-BR.vtt 692 B
Part 16-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.en.vtt 692 B
Part 15-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.zh-CN.vtt 692 B
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.pt-BR.vtt 691 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.pt-BR.vtt 691 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.pt-BR.vtt 690 B
Part 04-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.en.vtt 690 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.hr.vtt 690 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.pt-BR.vtt 688 B
Part 16-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.zh-CN.vtt 688 B
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.pt-BR.vtt 688 B
Part 02-Module 01-Lesson 01_Numbers and Strings/12. Ud1110 IntroPy L1 53 Lesson 1 Done!-y3dstGZWPgc.zh-CN.vtt 688 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.pt-BR.vtt 687 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.pt-BR.vtt 686 B
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.es-ES.vtt 686 B
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.en.vtt 685 B
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.ar.vtt 685 B
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.en.vtt 685 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.ar.vtt 684 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pt-BR.vtt 684 B
Part 04-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.ar.vtt 684 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.ar.vtt 684 B
Part 04-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.ar.vtt 683 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.zh-CN.vtt 683 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.ar.vtt 683 B
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.pt-BR.vtt 683 B
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.en.vtt 682 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.es-ES.vtt 682 B
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.ar.vtt 682 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 2-so5zydnbYEg.en.vtt 682 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.en.vtt 682 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.es-ES.vtt 681 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.pt-BR.vtt 680 B
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.zh-CN.vtt 680 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.es-ES.vtt 679 B
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.ar.vtt 679 B
Part 07-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.en.vtt 679 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.es-ES.vtt 679 B
Part 07-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.pt-BR.vtt 678 B
Part 12-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.ar.vtt 678 B
Part 07-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.en.vtt 677 B
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.ar.vtt 677 B
Part 08-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.pt-BR.vtt 677 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.th.vtt 677 B
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.zh-CN.vtt 677 B
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.zh-CN.vtt 677 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.zh-CN.vtt 676 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.zh-CN.vtt 675 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.ar.vtt 675 B
Part 04-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.en.vtt 675 B
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.ar.vtt 675 B
Part 14-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.zh-CN.vtt 675 B
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.en.vtt 675 B
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.pt-BR.vtt 673 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.zh-CN.vtt 673 B
Part 18-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.ar.vtt 673 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.ar.vtt 673 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.pt-BR.vtt 673 B
Part 16-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.zh-CN.vtt 672 B
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.pt-BR.vtt 672 B
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.es-ES.vtt 671 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.it.vtt 671 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.es-ES.vtt 671 B
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.pt-BR.vtt 671 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.ar.vtt 670 B
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.zh-CN.vtt 670 B
Part 16-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.ar.vtt 669 B
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.ja.vtt 669 B
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.ar.vtt 669 B
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.zh-CN.vtt 668 B
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.en.vtt 668 B
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.en.vtt 668 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.th.vtt 667 B
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.en.vtt 666 B
Part 16-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.en.vtt 666 B
Part 16-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.zh-CN.vtt 665 B
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.es-ES.vtt 665 B
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.ar.vtt 665 B
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.en.vtt 665 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.ar.vtt 665 B
Part 16-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.zh-CN.vtt 664 B
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.en.vtt 664 B
Part 11-Module 01-Lesson 02_Create A Git Repo/05. Create A Repo - Outro-h7j4STDFCjs.zh-CN.vtt 664 B
Part 14-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.en.vtt 663 B
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.ar.vtt 663 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.en.vtt 663 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.ar.vtt 662 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.hr.vtt 662 B
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.ar.vtt 662 B
Part 04-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.ar.vtt 662 B
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.zh-CN.vtt 662 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.ar.vtt 662 B
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.pt-BR.vtt 661 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.ja.vtt 661 B
Part 08-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.zh-CN.vtt 661 B
Part 16-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.pt-BR.vtt 660 B
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.pt-BR.vtt 660 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.zh-CN.vtt 660 B
Part 16-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.en.vtt 660 B
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.en.vtt 660 B
Part 08-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.en.vtt 660 B
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.en.vtt 658 B
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.en.vtt 658 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.en.vtt 658 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.en.vtt 658 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.zh-CN.vtt 658 B
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.ar.vtt 658 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.th.vtt 657 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.ja.vtt 657 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.es-ES.vtt 656 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.it.vtt 656 B
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.zh-CN.vtt 656 B
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.ar.vtt 656 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.en.vtt 656 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/21. Model Problems-Och80L_uNjU.zh-CN.vtt 656 B
Part 16-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.zh-CN.vtt 655 B
Part 04-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.en.vtt 655 B
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.ja.vtt 655 B
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.pt-BR.vtt 655 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.en.vtt 655 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.th.vtt 654 B
Part 16-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.pt-BR.vtt 654 B
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.ar.vtt 654 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.ja.vtt 653 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.pt-BR.vtt 653 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.th.vtt 653 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.en.vtt 653 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-a2GCyz_N0oY.ar.vtt 652 B
Part 18-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.ar.vtt 652 B
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.en.vtt 652 B
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.ar.vtt 652 B
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/01. Ud1110 IntroPy L201 Welcome Back!-oCCMSsCc4Iw.pt-BR.vtt 652 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.pt-BR.vtt 652 B
Part 11-Module 01-Lesson 06_Undoing Changes/05. Undoing Changes--_PPVk2UZMU.en.vtt 651 B
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 54 Content On Different Branches-Px6EUylw8Uw.en.vtt 651 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.ar.vtt 650 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.en.vtt 650 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.ar.vtt 650 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.zh-CN.vtt 650 B
Part 16-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.zh-CN.vtt 649 B
Part 07-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.zh-CN.vtt 649 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.ja.vtt 647 B
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.pt-BR.vtt 646 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.en.vtt 646 B
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.ja.vtt 646 B
Part 11-Module 01-Lesson 06_Undoing Changes/05. Undoing Changes--_PPVk2UZMU.pt-BR.vtt 646 B
Part 18-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.en.vtt 645 B
Part 16-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.zh-CN.vtt 645 B
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.ar.vtt 644 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.zh-CN.vtt 644 B
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.ja.vtt 644 B
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.pt-BR.vtt 644 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.zh-CN.vtt 644 B
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.en.vtt 644 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.pt-BR.vtt 644 B
Part 16-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.zh-CN.vtt 643 B
Part 02-Module 01-Lesson 03_Data Structures and Loops/01. Ud1110 IntroPy L301 Welcome To Lesson 3-ikOWhrOUgLc.pt-BR.vtt 643 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION 2-so5zydnbYEg.zh-CN.vtt 643 B
Part 04-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.zh-CN.vtt 643 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.pt-BR.vtt 642 B
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.pt-BR.vtt 641 B
Part 08-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.zh-CN.vtt 641 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.ar.vtt 640 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.en.vtt 640 B
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.hr.vtt 640 B
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 54 Content On Different Branches-Px6EUylw8Uw.zh-CN.vtt 639 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.en.vtt 639 B
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.pt-BR.vtt 639 B
Part 16-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.en.vtt 638 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.zh-CN.vtt 638 B
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.pt-BR.vtt 638 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-a2GCyz_N0oY.ja.vtt 637 B
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.hr.vtt 637 B
Part 02-Module 01-Lesson 03_Data Structures and Loops/01. Ud1110 IntroPy L301 Welcome To Lesson 3-ikOWhrOUgLc.en.vtt 637 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.pt-BR.vtt 637 B
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.pt-BR.vtt 636 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.pt-BR.vtt 636 B
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Coding inside the skeleton loop-MRPdqOwnqag.pt-BR.vtt 636 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.en.vtt 636 B
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.en.vtt 635 B
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.ar.vtt 635 B
Part 16-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.en.vtt 635 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.en.vtt 634 B
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.en.vtt 634 B
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.th.vtt 634 B
Part 04-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.zh-CN.vtt 633 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.en.vtt 633 B
Part 16-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.zh-CN.vtt 633 B
Part 07-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.zh-CN.vtt 633 B
Part 16-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.ja.vtt 632 B
Part 16-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.en-US.vtt 632 B
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.ar.vtt 632 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.ja.vtt 632 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.zh-CN.vtt 632 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.ar.vtt 631 B
Part 07-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.ar.vtt 631 B
Part 16-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.pt-BR.vtt 630 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.zh-CN.vtt 630 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.en.vtt 630 B
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.pt-BR.vtt 629 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.zh-CN.vtt 629 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.pt-BR.vtt 629 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.es-ES.vtt 629 B
Part 16-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.pt-BR.vtt 629 B
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.ja.vtt 628 B
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.pt-BR.vtt 628 B
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.en.vtt 628 B
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.pt-BR.vtt 628 B
Part 16-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.pt-BR.vtt 627 B
Part 07-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.zh-CN.vtt 627 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.ja.vtt 627 B
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.pt-BR.vtt 626 B
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.zh-CN.vtt 626 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.ar.vtt 626 B
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.en.vtt 626 B
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.it.vtt 625 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.ja.vtt 625 B
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.ar.vtt 624 B
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.ar.vtt 624 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.ar.vtt 623 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.ja.vtt 623 B
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.zh-CN.vtt 623 B
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.en.vtt 623 B
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.en.vtt 622 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.ar.vtt 622 B
Part 16-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.zh-CN.vtt 622 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.en.vtt 622 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.zh-CN.vtt 622 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.ja.vtt 621 B
Part 07-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.ja.vtt 620 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.zh-CN.vtt 620 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.pt-BR.vtt 620 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/19. Congratulations!-_FPpbuuW-1o.pt-BR.vtt 620 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.ar.vtt 620 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.en.vtt 619 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.it.vtt 618 B
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.pt-BR.vtt 618 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.ja.vtt 618 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.zh-CN.vtt 618 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.pt-BR.vtt 618 B
Part 04-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.zh-CN.vtt 617 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.en.vtt 617 B
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ru.vtt 617 B
Part 04-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.en.vtt 617 B
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ja.vtt 617 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.en-US.vtt 617 B
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 54 Content On Different Branches-Px6EUylw8Uw.pt-BR.vtt 617 B
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.en-US.vtt 617 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.zh-CN.vtt 616 B
Part 04-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.zh-CN.vtt 616 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.ar.vtt 616 B
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.zh-CN.vtt 616 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.ar.vtt 615 B
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.ja.vtt 614 B
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.en.vtt 613 B
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.en.vtt 613 B
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.zh-CN.vtt 613 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.pt-BR.vtt 612 B
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.ja.vtt 611 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.es-ES.vtt 611 B
Part 16-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.en.vtt 611 B
Part 07-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.zh-CN.vtt 611 B
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.zh-CN.vtt 610 B
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.en.vtt 610 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.en.vtt 610 B
Part 16-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.en.vtt 609 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.zh-CN.vtt 609 B
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.es-ES.vtt 608 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.ja.vtt 608 B
Part 12-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.ar.vtt 608 B
Part 06-Module 01-Lesson 01_Welcome to Term 2!/06. Introduction-fxNSn63xFvA.pt-BR.vtt 608 B
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.pt-BR.vtt 608 B
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/05. Introduction-fxNSn63xFvA.pt-BR.vtt 608 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.ar.vtt 607 B
Part 02-Module 01-Lesson 03_Data Structures and Loops/01. Ud1110 IntroPy L301 Welcome To Lesson 3-ikOWhrOUgLc.zh-CN.vtt 607 B
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.pt-BR.vtt 606 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.zh-CN.vtt 606 B
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.en.vtt 605 B
Part 07-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.ar.vtt 604 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.th.vtt 604 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.th.vtt 603 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.pt-BR.vtt 602 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.ar.vtt 602 B
Part 16-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.en.vtt 601 B
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.pt-BR.vtt 601 B
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.en.vtt 601 B
Part 07-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.zh-CN.vtt 600 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.pt-BR.vtt 600 B
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.en.vtt 600 B
Part 16-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.pt-BR.vtt 599 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.hr.vtt 599 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.ar.vtt 599 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.en.vtt 599 B
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.pt-BR.vtt 599 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.it.vtt 598 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.en.vtt 598 B
Part 04-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.en.vtt 598 B
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.pt-BR.vtt 598 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.pt-BR.vtt 597 B
Part 11-Module 01-Lesson 06_Undoing Changes/05. Undoing Changes--_PPVk2UZMU.zh-CN.vtt 597 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.ja.vtt 597 B
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.ar.vtt 597 B
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.ar.vtt 597 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.ja.vtt 596 B
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.en.vtt 596 B
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.zh-CN.vtt 596 B
Part 16-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.en.vtt 596 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.es-ES.vtt 595 B
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.en.vtt 595 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-e_8DmUBHAao.ar.vtt 595 B
Part 07-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.ja.vtt 594 B
Part 07-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.zh-CN.vtt 594 B
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.ja.vtt 594 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.pt-BR.vtt 593 B
Part 16-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.zh-CN.vtt 593 B
Part 16-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.zh-CN.vtt 593 B
Part 07-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.ja.vtt 592 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.en.vtt 591 B
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.en.vtt 591 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.ar.vtt 591 B
Part 16-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.zh-CN.vtt 589 B
Part 06-Module 01-Lesson 01_Welcome to Term 2!/06. Introduction-fxNSn63xFvA.en.vtt 589 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.pt-BR.vtt 589 B
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/05. Introduction-fxNSn63xFvA.en.vtt 589 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.ja.vtt 589 B
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.zh-CN.vtt 589 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.pt-BR.vtt 589 B
Part 07-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.ja.vtt 588 B
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.ar.vtt 588 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.ja.vtt 587 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.zh-CN.vtt 587 B
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.en.vtt 587 B
Part 04-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.en.vtt 586 B
Part 16-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.zh-CN.vtt 584 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.ja.vtt 584 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.ar.vtt 584 B
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.pt-BR.vtt 584 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.ar.vtt 583 B
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.ar.vtt 583 B
Part 18-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.pt-BR.vtt 583 B
Part 04-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.zh-CN.vtt 582 B
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.ar.vtt 582 B
Part 16-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.zh-CN.vtt 582 B
Part 04-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.pt-BR.vtt 582 B
Part 07-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.ja.vtt 582 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.zh-CN.vtt 582 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.ar.vtt 582 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.en.vtt 581 B
Part 16-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.zh-CN.vtt 580 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.zh-Hans.vtt 579 B
Part 04-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.pt-BR.vtt 579 B
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.zh-CN.vtt 579 B
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.en.vtt 579 B
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.pt-BR.vtt 579 B
Part 16-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.zh-CN.vtt 579 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.zh-CN.vtt 579 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.th.vtt 579 B
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.en.vtt 579 B
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.ja.vtt 578 B
Part 16-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.zh-CN.vtt 578 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.th.vtt 578 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.zh-CN.vtt 577 B
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.pt-BR.vtt 577 B
Part 04-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.pt-BR.vtt 576 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-a2GCyz_N0oY.pt-BR.vtt 576 B
Part 16-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.zh-CN.vtt 575 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.hr.vtt 575 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.en.vtt 575 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.es-ES.vtt 575 B
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.en.vtt 575 B
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/01. Ud1110 IntroPy L201 Welcome Back!-oCCMSsCc4Iw.en.vtt 574 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-a2GCyz_N0oY.en-US.vtt 574 B
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.pt-BR.vtt 573 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.ja.vtt 573 B
Part 16-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.en.vtt 573 B
Part 04-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.en.vtt 572 B
Part 04-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.zh-CN.vtt 572 B
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.ja.vtt 572 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.en.vtt 571 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.it.vtt 571 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.pt-BR.vtt 571 B
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.pt-BR.vtt 570 B
Part 16-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.zh-CN.vtt 570 B
Part 16-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.ar.vtt 570 B
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.en.vtt 569 B
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Coding inside the skeleton loop-MRPdqOwnqag.en.vtt 569 B
Part 18-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.zh-CN.vtt 569 B
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.en-US.vtt 569 B
Part 16-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.pt-BR.vtt 568 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.pt-BR.vtt 568 B
Part 04-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.pt-BR.vtt 567 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.pt-BR.vtt 567 B
Part 04-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.pt-BR.vtt 567 B
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.en.vtt 566 B
Part 04-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.zh-CN.vtt 566 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.es-ES.vtt 566 B
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.ar.vtt 566 B
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.en.vtt 566 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.es-ES.vtt 565 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-a2GCyz_N0oY.en.vtt 565 B
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.hr.vtt 565 B
Part 04-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.en.vtt 564 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.zh-CN.vtt 563 B
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.pt-BR.vtt 563 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.pt-BR.vtt 563 B
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.ar.vtt 563 B
Part 07-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.zh-CN.vtt 562 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.ar.vtt 562 B
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.en.vtt 561 B
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.ar.vtt 561 B
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.pt-BR.vtt 561 B
Part 16-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.zh-CN.vtt 560 B
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.pt-BR.vtt 560 B
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.es-ES.vtt 560 B
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.ar.vtt 559 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.en.vtt 558 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.zh-CN.vtt 558 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.ar.vtt 558 B
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.ja.vtt 557 B
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.zh-CN.vtt 556 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.zh-CN.vtt 556 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.en.vtt 555 B
Part 04-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.zh-CN.vtt 554 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.th.vtt 554 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price-Ck4i1Yk4pT0.ar.vtt 553 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.en.vtt 553 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.zh-CN.vtt 553 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.zh-CN.vtt 553 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.zh-CN.vtt 552 B
Part 16-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.zh-CN.vtt 552 B
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.it.vtt 552 B
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.zh-CN.vtt 552 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.pt-BR.vtt 552 B
Part 12-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.pt-BR.vtt 551 B
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.en.vtt 550 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.zh-CN.vtt 549 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.en.vtt 549 B
Part 16-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.pt-BR.vtt 549 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.en.vtt 549 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.ar.vtt 549 B
Part 07-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.ar.vtt 548 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.th.vtt 548 B
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.zh-CN.vtt 547 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.zh-CN.vtt 547 B
Part 16-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.pt-BR.vtt 547 B
Part 16-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.zh-CN.vtt 547 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.ar.vtt 547 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.pt-BR.vtt 547 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.pt-BR.vtt 547 B
Part 09-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.en.vtt 546 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.ar.vtt 544 B
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals/01. Ud1110 IntroPy L201 Welcome Back!-oCCMSsCc4Iw.zh-CN.vtt 544 B
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.ar.vtt 543 B
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.ar.vtt 543 B
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.en.vtt 543 B
Part 16-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.zh-CN.vtt 543 B
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.ar.vtt 542 B
Part 04-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.pt-BR.vtt 541 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.th.vtt 541 B
Part 09-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.pt-BR.vtt 541 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.ja.vtt 541 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.en.vtt 540 B
Part 16-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.pt-BR.vtt 540 B
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.pt-BR.vtt 540 B
Part 16-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.zh-CN.vtt 539 B
Part 16-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.zh-CN.vtt 539 B
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.ar.vtt 539 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.hr.vtt 539 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.zh-CN.vtt 539 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.es-ES.vtt 538 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.zh-CN.vtt 538 B
Part 12-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.pt-BR.vtt 538 B
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.pt-BR.vtt 538 B
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.ar.vtt 538 B
Part 16-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.zh-CN.vtt 537 B
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.en.vtt 537 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.en.vtt 536 B
Part 16-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.ar.vtt 536 B
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.en.vtt 536 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.zh-CN.vtt 536 B
Part 04-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.zh-CN.vtt 536 B
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.ja.vtt 535 B
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.es-ES.vtt 535 B
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.ar.vtt 535 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.ar.vtt 535 B
Part 16-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.zh-CN.vtt 534 B
Part 18-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.ar.vtt 534 B
Part 04-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.en.vtt 534 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.en.vtt 534 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.ar.vtt 533 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.pt-BR.vtt 533 B
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.pt-BR.vtt 533 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.es-ES.vtt 533 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.ar.vtt 533 B
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.ja.vtt 532 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.ar.vtt 532 B
Part 04-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.zh-CN.vtt 532 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.ar.vtt 532 B
Part 04-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.zh-CN.vtt 532 B
Part 16-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.zh-CN.vtt 531 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.ar.vtt 531 B
Part 04-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.zh-CN.vtt 531 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.ja.vtt 531 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.es-ES.vtt 531 B
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.pt-BR.vtt 530 B
Part 04-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.en.vtt 530 B
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.hr.vtt 530 B
Part 16-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.zh-CN.vtt 530 B
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/05. Coding inside the skeleton loop-MRPdqOwnqag.zh-CN.vtt 530 B
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.pt-BR.vtt 529 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.es-ES.vtt 529 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.zh-CN.vtt 529 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.pt-BR.vtt 529 B
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.zh-CN.vtt 528 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.en.vtt 528 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-a2GCyz_N0oY.zh-CN.vtt 528 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.ja.vtt 527 B
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. Projects-1-E_ZYovKeI.en.vtt 527 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.en.vtt 527 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.ja.vtt 527 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.pt-BR.vtt 526 B
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.zh-CN.vtt 526 B
Part 04-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.pt-BR.vtt 526 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.ar.vtt 526 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.ja.vtt 525 B
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.en.vtt 524 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.ar.vtt 524 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.en.vtt 524 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.pt-BR.vtt 523 B
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.en.vtt 523 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.pt-BR.vtt 523 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.pt-BR.vtt 523 B
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.en.vtt 523 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.zh-CN.vtt 522 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.zh-CN.vtt 522 B
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.pt-BR.vtt 522 B
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.ar.vtt 521 B
Part 04-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.zh-CN.vtt 521 B
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.ar.vtt 521 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.pt-BR.vtt 520 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.en.vtt 518 B
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.pt-BR.vtt 518 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.ar.vtt 518 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.ar.vtt 518 B
Part 04-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.hr.vtt 517 B
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.pt-BR.vtt 517 B
Part 10-Module 01-Lesson 01_Congratulations & Next Steps/03. Projects-1-E_ZYovKeI.pt-BR.vtt 516 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.ar.vtt 516 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.pt-BR.vtt 516 B
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.zh-CN.vtt 516 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.es-ES.vtt 516 B
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.ar.vtt 515 B
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!/05. Introduction-fxNSn63xFvA.zh-CN.vtt 513 B
Part 06-Module 01-Lesson 01_Welcome to Term 2!/06. Introduction-fxNSn63xFvA.zh-CN.vtt 513 B
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.en.vtt 513 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.en.vtt 513 B
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.en.vtt 512 B
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.ar.vtt 512 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-b7oUjvNJWCc.ar.vtt 511 B
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.ar.vtt 510 B
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.en.vtt 510 B
Part 16-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.zh-CN.vtt 510 B
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.ar.vtt 509 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.zh-CN.vtt 508 B
Part 18-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.pt-BR.vtt 508 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.zh-CN.vtt 508 B
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.ar.vtt 508 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.en.vtt 508 B
Part 16-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.en.vtt 507 B
Part 16-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.zh-CN.vtt 507 B
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.pt-BR.vtt 507 B
Part 04-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.zh-CN.vtt 505 B
Part 16-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.ar.vtt 505 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.zh-CN.vtt 505 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.it.vtt 504 B
Part 04-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.zh-CN.vtt 504 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.zh-CN.vtt 504 B
Part 04-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.zh-CN.vtt 503 B
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.pt-BR.vtt 503 B
Part 09-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.zh-CN.vtt 503 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.zh-CN.vtt 503 B
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.es-ES.vtt 502 B
Part 07-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.en.vtt 502 B
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.zh-CN.vtt 502 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-aUc0FKD4834.ar.vtt 501 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.pt-BR.vtt 501 B
Part 07-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.ja.vtt 501 B
Part 12-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.en.vtt 501 B
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.pt-BR.vtt 500 B
Part 16-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.zh-CN.vtt 499 B
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.zh-CN.vtt 499 B
Part 04-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.zh-CN.vtt 499 B
Part 16-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.zh-CN.vtt 498 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.pt-BR.vtt 498 B
Part 07-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.pt-BR.vtt 497 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.ar.vtt 497 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.pt-BR.vtt 497 B
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.pt-BR.vtt 497 B
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.zh-CN.vtt 497 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.en.vtt 497 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.ar.vtt 496 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.pt-BR.vtt 496 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.en.vtt 496 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.pt-BR.vtt 495 B
Part 04-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.zh-CN.vtt 495 B
Part 04-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.en.vtt 495 B
Part 07-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.en.vtt 495 B
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.pt-BR.vtt 494 B
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.ja.vtt 494 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.ar.vtt 494 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.ar.vtt 493 B
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.es-ES.vtt 493 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.zh-CN.vtt 492 B
Part 07-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.pt-BR.vtt 492 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.ja.vtt 492 B
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.ar.vtt 491 B
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.en.vtt 491 B
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.pt-BR.vtt 491 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.en.vtt 491 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.ja.vtt 491 B
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.en.vtt 490 B
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.zh-CN.vtt 490 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.zh-CN.vtt 490 B
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.ar.vtt 490 B
Part 12-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.ar.vtt 490 B
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.en.vtt 489 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.pt-BR.vtt 489 B
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.pt-BR.vtt 488 B
Part 16-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.zh-CN.vtt 488 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.pt-BR.vtt 488 B
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.ja.vtt 487 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.pt-BR.vtt 486 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.en.vtt 486 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.en.vtt 486 B
Part 16-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.zh-CN.vtt 485 B
Part 16-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.zh-CN.vtt 485 B
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.zh-CN.vtt 485 B
Part 04-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.en.vtt 484 B
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.zh-CN.vtt 484 B
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.pt-BR.vtt 484 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.pt-BR.vtt 483 B
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.pt-BR.vtt 483 B
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.en.vtt 483 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.ja.vtt 483 B
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.ar.vtt 483 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.en-US.vtt 482 B
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.en.vtt 482 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.pt-BR.vtt 482 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.ar.vtt 482 B
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.pt-BR.vtt 482 B
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.en-US.vtt 482 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.pt-BR.vtt 481 B
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.ar.vtt 481 B
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.ar.vtt 480 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.es-ES.vtt 480 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.th.vtt 480 B
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.en.vtt 479 B
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.ar.vtt 479 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.ar.vtt 479 B
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.pt-BR.vtt 478 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.pt-BR.vtt 478 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.es-ES.vtt 478 B
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.pt-BR.vtt 478 B
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.ja.vtt 478 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.en.vtt 478 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.it.vtt 476 B
Part 12-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.en.vtt 476 B
Part 07-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.ja.vtt 476 B
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.pt-BR.vtt 474 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.ar.vtt 474 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.ar.vtt 474 B
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.pt-BR.vtt 474 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.ar.vtt 473 B
Part 12-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.zh-CN.vtt 473 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.es-ES.vtt 473 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.ar.vtt 473 B
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.en.vtt 473 B
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.ja.vtt 473 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.pt-BR.vtt 473 B
Part 18-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.en.vtt 473 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.en.vtt 473 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.pt-BR.vtt 473 B
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.ar.vtt 473 B
Part 04-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.zh-CN.vtt 473 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.en-US.vtt 472 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-e_8DmUBHAao.ja.vtt 472 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.ar.vtt 472 B
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.en.vtt 472 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.zh-CN.vtt 472 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.ja.vtt 472 B
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.en.vtt 472 B
Part 04-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.en-US.vtt 472 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.ar.vtt 471 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.es-ES.vtt 471 B
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.ar.vtt 471 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.es-ES.vtt 471 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.en.vtt 470 B
Part 16-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.en.vtt 470 B
Part 16-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.zh-CN.vtt 470 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.hr.vtt 469 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.en.vtt 469 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.ja.vtt 469 B
Part 04-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.en.vtt 469 B
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.en.vtt 468 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.en.vtt 468 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.en.vtt 468 B
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.en.vtt 468 B
Part 18-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.en.vtt 467 B
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.zh-CN.vtt 467 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.zh-CN.vtt 467 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.es-ES.vtt 466 B
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.ja.vtt 466 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.ar.vtt 466 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.ja.vtt 466 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.pt-BR.vtt 465 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.en.vtt 464 B
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.ar.vtt 464 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.ar.vtt 463 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.ar.vtt 462 B
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.en.vtt 462 B
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.ar.vtt 462 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.en.vtt 461 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-b7oUjvNJWCc.ja.vtt 461 B
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.pt-BR.vtt 461 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.zh-CN.vtt 460 B
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.pt-BR.vtt 460 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.zh-CN.vtt 460 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.ar.vtt 459 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.ar.vtt 459 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.es-ES.vtt 459 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.en.vtt 458 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.ar.vtt 458 B
Part 04-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.zh-CN.vtt 458 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.en.vtt 458 B
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.en.vtt 458 B
Part 07-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.zh-CN.vtt 458 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.ja.vtt 458 B
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.pt-BR.vtt 457 B
Part 12-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.pt-BR.vtt 457 B
Part 16-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.en.vtt 457 B
Part 18-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.zh-CN.vtt 456 B
Part 08-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.ar.vtt 456 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.zh-CN.vtt 456 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.ar.vtt 456 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.it.vtt 456 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-e_8DmUBHAao.pt-BR.vtt 456 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.zh-CN.vtt 456 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.es-ES.vtt 455 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.en.vtt 455 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.ar.vtt 455 B
Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.ar.vtt 455 B
README.txt 454 B
Part 16-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.zh-CN.vtt 454 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-b7oUjvNJWCc.pt-BR.vtt 454 B
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.pt-BR.vtt 454 B
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.pt-BR.vtt 454 B
Part 12-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.pt-BR.vtt 453 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.en.vtt 453 B
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.en.vtt 453 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.hr.vtt 453 B
Part 07-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.pt-BR.vtt 452 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.it.vtt 452 B
Part 04-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.zh-CN.vtt 451 B
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.en.vtt 451 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.es-ES.vtt 451 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.zh-CN.vtt 451 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.pt-BR.vtt 451 B
Part 07-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.ja.vtt 451 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price-Ck4i1Yk4pT0.ja.vtt 450 B
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.en.vtt 449 B
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.en.vtt 449 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.ja.vtt 449 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.en.vtt 449 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price-Ck4i1Yk4pT0.en-US.vtt 449 B
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.ar.vtt 447 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.pt-BR.vtt 447 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.pt-BR.vtt 447 B
Part 16-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.ar.vtt 447 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.th.vtt 447 B
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.zh-CN.vtt 446 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.ar.vtt 446 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.ar.vtt 445 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price-Ck4i1Yk4pT0.en.vtt 445 B
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.pt-BR.vtt 445 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.ja.vtt 444 B
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.ar.vtt 444 B
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.pt-BR.vtt 444 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.it.vtt 444 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.ja.vtt 443 B
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.zh-CN.vtt 442 B
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.en.vtt 442 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.pt-BR.vtt 442 B
Part 04-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.zh-CN.vtt 441 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.th.vtt 441 B
Part 16-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.zh-CN.vtt 440 B
Part 03-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.zh-CN.vtt 440 B
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.pt-BR.vtt 440 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-b7oUjvNJWCc.en.vtt 440 B
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.pt-BR.vtt 439 B
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.ar.vtt 438 B
Part 12-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.zh-CN.vtt 438 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-e_8DmUBHAao.en.vtt 437 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.ar.vtt 437 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.ar.vtt 436 B
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.pt-BR.vtt 436 B
Part 07-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.en.vtt 436 B
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.ar.vtt 436 B
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.en.vtt 435 B
Part 12-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.en.vtt 435 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.it.vtt 435 B
Part 16-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.pt-BR.vtt 435 B
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.zh-CN.vtt 434 B
Part 16-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.ja.vtt 434 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.it.vtt 433 B
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.pt-BR.vtt 433 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-aUc0FKD4834.ja.vtt 433 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.pt-BR.vtt 433 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.en.vtt 433 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.en.vtt 432 B
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.zh-CN.vtt 432 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-aUc0FKD4834.pt-BR.vtt 432 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price--P5lMGuVA6U.ja.vtt 432 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.ja.vtt 431 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.zh-CN.vtt 431 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.en.vtt 430 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price-Ck4i1Yk4pT0.pt-BR.vtt 429 B
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.en.vtt 428 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.ja.vtt 428 B
Part 16-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.en.vtt 428 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.en.vtt 428 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.pt-BR.vtt 427 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.en.vtt 427 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.pt-BR.vtt 427 B
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.pt-BR.vtt 426 B
Part 07-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.zh-CN.vtt 426 B
Part 04-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.zh-CN.vtt 426 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.es-ES.vtt 426 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price-Ck4i1Yk4pT0.zh-CN.vtt 426 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.zh-CN.vtt 426 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.ja.vtt 425 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.en.vtt 425 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.es-ES.vtt 425 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.zh-CN.vtt 425 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.hr.vtt 425 B
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.zh-CN.vtt 425 B
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.ar.vtt 425 B
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.ar.vtt 425 B
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.zh-CN.vtt 425 B
Part 16-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.zh-CN.vtt 424 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.es-ES.vtt 424 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.en.vtt 424 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.ja.vtt 424 B
Part 16-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.ar.vtt 423 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.ar.vtt 423 B
Part 16-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.pt-BR.vtt 423 B
Part 18-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.en.vtt 423 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.th.vtt 423 B
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.en.vtt 422 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.ar.vtt 422 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.pt-BR.vtt 422 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.it.vtt 422 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.zh-CN.vtt 422 B
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.zh-CN.vtt 422 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.ar.vtt 422 B
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.ar.vtt 422 B
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.pt-BR.vtt 421 B
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.ar.vtt 421 B
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.en.vtt 421 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.ar.vtt 420 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.ja.vtt 420 B
Part 16-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.zh-CN.vtt 420 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.zh-CN.vtt 420 B
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.en.vtt 419 B
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.ja.vtt 419 B
Part 16-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.ar.vtt 419 B
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.en.vtt 419 B
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.en.vtt 418 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.pt-BR.vtt 418 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.ja.vtt 417 B
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.pt-BR.vtt 417 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.pt-BR.vtt 417 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.es-ES.vtt 417 B
Part 09-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.zh-CN.vtt 416 B
Part 07-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.zh-CN.vtt 416 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.ja.vtt 416 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.en.vtt 416 B
Part 16-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.zh-CN.vtt 416 B
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.zh-CN.vtt 415 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.ja.vtt 415 B
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.en.vtt 415 B
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.pt-BR.vtt 415 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.th.vtt 415 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.en.vtt 414 B
Part 16-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.zh-CN.vtt 414 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-e_8DmUBHAao.zh-CN.vtt 414 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.it.vtt 414 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.ar.vtt 413 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.es-ES.vtt 412 B
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.en.vtt 412 B
Part 18-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.pt-BR.vtt 411 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.zh-CN.vtt 411 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.ar.vtt 411 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.ja.vtt 410 B
Part 12-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.zh-CN.vtt 410 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.pt-BR.vtt 410 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.pt-BR.vtt 410 B
Part 18-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.zh-CN.vtt 410 B
Part 16-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.pt-BR.vtt 410 B
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.it.vtt 409 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.zh-CN.vtt 409 B
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.en.vtt 409 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.zh-CN.vtt 409 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.zh-CN.vtt 409 B
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.zh-CN.vtt 408 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.ar.vtt 408 B
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.ar.vtt 408 B
Part 04-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.zh-CN.vtt 408 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.zh-CN.vtt 408 B
Part 16-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.zh-CN.vtt 408 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-aUc0FKD4834.en.vtt 407 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-b7oUjvNJWCc.zh-CN.vtt 407 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.ar.vtt 406 B
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.pt-BR.vtt 406 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.pt-BR.vtt 406 B
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.es-ES.vtt 406 B
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.en.vtt 406 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.pt-BR.vtt 405 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.en.vtt 405 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.ar.vtt 405 B
Part 16-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.zh-CN.vtt 405 B
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.pt-BR.vtt 405 B
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.pt-BR.vtt 405 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.ar.vtt 404 B
Part 16-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.zh-CN.vtt 404 B
Part 16-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.en.vtt 404 B
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.zh-CN.vtt 403 B
Part 04-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.ja.vtt 403 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.zh-CN.vtt 403 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.ar.vtt 402 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price--P5lMGuVA6U.ar.vtt 402 B
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.ar.vtt 402 B
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.pt-BR.vtt 402 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.pt-BR.vtt 401 B
Part 16-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.zh-CN.vtt 401 B
Part 03-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.zh-CN.vtt 401 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.zh-CN.vtt 400 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.zh-CN.vtt 399 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.ar.vtt 399 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.ar.vtt 399 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.en.vtt 399 B
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.en.vtt 399 B
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.zh-CN.vtt 399 B
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.ja.vtt 398 B
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.ja.vtt 398 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.th.vtt 398 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.en.vtt 397 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.pt-BR.vtt 397 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.en.vtt 397 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.ja.vtt 397 B
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.pt-BR.vtt 396 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.pt-BR.vtt 396 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.ar.vtt 396 B
Part 16-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.zh-CN.vtt 396 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.ja.vtt 395 B
Part 16-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.en.vtt 395 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.ar.vtt 395 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.ja.vtt 395 B
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.en.vtt 394 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.en.vtt 394 B
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.ar.vtt 393 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.pt-BR.vtt 393 B
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.en-US.vtt 393 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.th.vtt 393 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.pt-BR.vtt 393 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.es-ES.vtt 393 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.ja.vtt 392 B
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.pt-BR.vtt 392 B
Part 12-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.zh-CN.vtt 392 B
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.ar.vtt 391 B
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.en.vtt 391 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.pt-BR.vtt 391 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.ja.vtt 390 B
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.es-ES.vtt 390 B
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.pt-BR.vtt 389 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.es-ES.vtt 389 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.zh-CN.vtt 389 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.ja.vtt 389 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.ja.vtt 389 B
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.ja.vtt 389 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.zh-CN.vtt 389 B
Part 18-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.zh-CN.vtt 389 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.es-ES.vtt 388 B
Part 16-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.ar.vtt 388 B
Part 04-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.ar.vtt 387 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.en.vtt 387 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.ar.vtt 387 B
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.en.vtt 386 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.pt-BR.vtt 386 B
Part 16-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.zh-CN.vtt 385 B
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.ar.vtt 385 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.hr.vtt 384 B
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.pt-BR.vtt 383 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.pt-BR.vtt 383 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.hr.vtt 383 B
Part 16-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.pt-BR.vtt 382 B
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.en.vtt 382 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.it.vtt 382 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.en.vtt 382 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.pt-BR.vtt 381 B
Part 04-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.zh-CN.vtt 380 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.zh-CN.vtt 380 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.pt-BR.vtt 379 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.zh-CN.vtt 379 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.zh-CN.vtt 378 B
Part 04-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.zh-CN.vtt 378 B
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.en.vtt 377 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.pt-BR.vtt 377 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.pt-BR.vtt 377 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.pt-BR.vtt 377 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.zh-CN.vtt 376 B
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.pt-BR.vtt 376 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.pt-BR.vtt 376 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.pt-BR.vtt 375 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.it.vtt 375 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.ja.vtt 374 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.pt-BR.vtt 374 B
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.ar.vtt 373 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.pt-BR.vtt 373 B
Part 07-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.zh-CN.vtt 373 B
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.ja.vtt 373 B
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.en.vtt 373 B
Part 16-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.zh-CN.vtt 372 B
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.ja.vtt 372 B
Part 16-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.zh-CN.vtt 372 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.it.vtt 372 B
Part 16-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.zh-CN.vtt 371 B
Part 12-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.en.vtt 371 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.ja.vtt 371 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.en.vtt 371 B
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.pt-BR.vtt 370 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.en.vtt 370 B
Part 08-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.pt-BR.vtt 370 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.ja.vtt 370 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.zh-CN.vtt 369 B
Part 04-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.zh-CN.vtt 369 B
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.pt-BR.vtt 369 B
Part 16-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.zh-CN.vtt 369 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.en.vtt 368 B
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.en.vtt 368 B
Part 16-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.en.vtt 368 B
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.pt-BR.vtt 367 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.zh-CN.vtt 367 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.ar.vtt 367 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.es-ES.vtt 367 B
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.zh-CN.vtt 366 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.pt-BR.vtt 366 B
Part 16-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.zh-CN.vtt 366 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.zh-CN.vtt 366 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.es-ES.vtt 366 B
Part 16-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.zh-CN.vtt 364 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.en.vtt 364 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.ar.vtt 364 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.zh-CN.vtt 364 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.en.vtt 364 B
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.pt-BR.vtt 363 B
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.ar.vtt 362 B
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.zh-CN.vtt 362 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.pt-BR.vtt 362 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.zh-CN.vtt 362 B
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.en.vtt 362 B
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.pt-BR.vtt 362 B
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.zh-CN.vtt 361 B
Part 16-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.zh-CN.vtt 361 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.en.vtt 360 B
Part 16-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.ja.vtt 360 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.pt-BR.vtt 360 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.es-ES.vtt 360 B
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.ar.vtt 360 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.th.vtt 359 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.it.vtt 359 B
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.ar.vtt 359 B
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.ar.vtt 359 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.en.vtt 358 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.es-ES.vtt 358 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.ja.vtt 357 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.en.vtt 357 B
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.ar.vtt 357 B
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.ar.vtt 357 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.es-ES.vtt 357 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.ar.vtt 357 B
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.ja.vtt 357 B
Part 12-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.zh-CN.vtt 357 B
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.ja.vtt 357 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.es-ES.vtt 357 B
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.ar.vtt 356 B
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.ar.vtt 356 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.pt-BR.vtt 356 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.es-ES.vtt 356 B
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.zh-CN.vtt 356 B
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.en.vtt 355 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.pt-BR.vtt 355 B
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.zh-CN.vtt 355 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.zh-CN.vtt 355 B
Part 16-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.zh-CN.vtt 355 B
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.pt-BR.vtt 355 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.es-ES.vtt 355 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.ar.vtt 355 B
Part 16-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.zh-CN.vtt 355 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.ar.vtt 354 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.pt-BR.vtt 354 B
Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.pt-BR.vtt 354 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.pt-BR.vtt 354 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.th.vtt 354 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.en.vtt 354 B
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.en.vtt 353 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.ja.vtt 353 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.ar.vtt 352 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.zh-CN.vtt 352 B
Part 16-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.zh-CN.vtt 352 B
Part 04-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.zh-CN.vtt 352 B
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.ar.vtt 352 B
Part 04-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.zh-CN.vtt 351 B
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.en.vtt 351 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.ja.vtt 351 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.ja.vtt 351 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.es-ES.vtt 350 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.en.vtt 350 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.ja.vtt 350 B
Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.en.vtt 350 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.ja.vtt 350 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.pt-BR.vtt 349 B
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.pt-BR.vtt 349 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.en.vtt 349 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.en.vtt 349 B
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.en.vtt 348 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.es-ES.vtt 348 B
Part 04-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.zh-CN.vtt 348 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.es-ES.vtt 348 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.en.vtt 347 B
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.en.vtt 346 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.en.vtt 346 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.zh-CN.vtt 346 B
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.ja.vtt 345 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.ja.vtt 345 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/19. Linear Models in R-aUc0FKD4834.zh-CN.vtt 345 B
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.ar.vtt 345 B
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.pt-BR.vtt 344 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.pt-BR.vtt 344 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price--P5lMGuVA6U.zh-CN.vtt 344 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.en.vtt 343 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.th.vtt 342 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.ar.vtt 342 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.en.vtt 342 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price--P5lMGuVA6U.pt-BR.vtt 342 B
Part 16-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.zh-CN.vtt 342 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.en.vtt 342 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.ar.vtt 341 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.zh-CN.vtt 341 B
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.pt-BR.vtt 341 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.it.vtt 341 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.en.vtt 341 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.ar.vtt 340 B
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.pt-BR.vtt 340 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.en.vtt 340 B
Part 07-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.ja.vtt 339 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.th.vtt 339 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.ar.vtt 339 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.pt-BR.vtt 339 B
Part 16-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.zh-CN.vtt 339 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.en.vtt 339 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.en.vtt 339 B
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.it.vtt 338 B
Part 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.es-ES.vtt 337 B
Part 16-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.ar.vtt 337 B
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.pt-BR.vtt 337 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.en.vtt 337 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.pt-BR.vtt 337 B
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.en.vtt 337 B
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.en.vtt 337 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.ar.vtt 336 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.en.vtt 336 B
Part 07-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.zh-CN.vtt 336 B
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.ja.vtt 336 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.pt-BR.vtt 335 B
Part 16-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.zh-CN.vtt 335 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.pt-BR.vtt 335 B
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.zh-CN.vtt 335 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.zh-CN.vtt 335 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.ar.vtt 334 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.ja.vtt 334 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.zh-CN.vtt 333 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.es-ES.vtt 333 B
Part 04-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.zh-CN.vtt 333 B
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.ja.vtt 332 B
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.en.vtt 332 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price--P5lMGuVA6U.en.vtt 332 B
Part 07-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.zh-CN.vtt 332 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.pt-BR.vtt 332 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.es-ES.vtt 332 B
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.zh-CN.vtt 332 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.en.vtt 331 B
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.pt-BR.vtt 331 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.ja.vtt 331 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.zh-CN.vtt 331 B
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.pt-BR.vtt 331 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.zh-CN.vtt 331 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.en.vtt 331 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.ja.vtt 329 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.es-ES.vtt 329 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.pt-BR.vtt 329 B
Part 16-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.zh-CN.vtt 328 B
Part 16-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.ar.vtt 327 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.ja.vtt 327 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.es-ES.vtt 327 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.zh-CN.vtt 327 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.ja.vtt 326 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.ar.vtt 326 B
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.pt-BR.vtt 326 B
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.ar.vtt 326 B
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.pt-BR.vtt 326 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.ja.vtt 326 B
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.en.vtt 325 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.ja.vtt 325 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.en.vtt 325 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.zh-CN.vtt 325 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.ar.vtt 325 B
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.en.vtt 325 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.pt-BR.vtt 324 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.it.vtt 324 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.ja.vtt 323 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.zh-CN.vtt 323 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.ar.vtt 323 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.en.vtt 322 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.en-US.vtt 321 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.en.vtt 321 B
Part 08-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.en.vtt 320 B
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.en.vtt 320 B
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.en.vtt 320 B
Part 04-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.zh-CN.vtt 320 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.hr.vtt 319 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.zh-CN.vtt 319 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.zh-CN.vtt 319 B
Part 04-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.en.vtt 319 B
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.ar.vtt 319 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.en.vtt 319 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.ar.vtt 319 B
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.ar.vtt 319 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.es-ES.vtt 318 B
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.pt-BR.vtt 318 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.en.vtt 318 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.en.vtt 317 B
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.ar.vtt 317 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.pt-BR.vtt 317 B
Part 16-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.zh-CN.vtt 316 B
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.en.vtt 316 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.ja.vtt 316 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.zh-CN.vtt 316 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.ja.vtt 315 B
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.en.vtt 315 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.it.vtt 315 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.ar.vtt 315 B
Part 16-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.zh-CN.vtt 315 B
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.en.vtt 315 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.ja.vtt 314 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.it.vtt 314 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.zh-CN.vtt 314 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.ja.vtt 314 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.en.vtt 313 B
Part 04-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.hr.vtt 312 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.zh-CN.vtt 312 B
Part 16-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.en.vtt 312 B
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.zh-CN.vtt 312 B
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.ar.vtt 312 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.it.vtt 311 B
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.pt-BR.vtt 311 B
Part 16-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.zh-CN.vtt 311 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.ja.vtt 310 B
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.en.vtt 310 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.en.vtt 310 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.zh-CN.vtt 309 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.ar.vtt 309 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.pt-BR.vtt 309 B
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.pt-BR.vtt 309 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-W96zaGEma7o.ar.vtt 308 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.zh-CN.vtt 308 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.it.vtt 308 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.it.vtt 307 B
Part 16-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.pt-BR.vtt 307 B
Part 04-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.pt-BR.vtt 307 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.en.vtt 307 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.pt-BR.vtt 307 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.zh-CN.vtt 307 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.en.vtt 306 B
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.pt-BR.vtt 306 B
Part 16-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.ar.vtt 306 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.zh-CN.vtt 306 B
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.en.vtt 306 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.pt-BR.vtt 305 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.th.vtt 305 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.pt-BR.vtt 305 B
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.pt-BR.vtt 305 B
Part 16-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.zh-CN.vtt 305 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.hr.vtt 305 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.ja.vtt 305 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.zh-CN.vtt 305 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.ja.vtt 305 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.ja.vtt 304 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.zh-CN.vtt 304 B
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.ar.vtt 304 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.ja.vtt 304 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.ar.vtt 303 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.zh-CN.vtt 303 B
Part 04-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.zh-CN.vtt 303 B
Part 16-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.zh-CN.vtt 303 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.ar.vtt 303 B
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.en.vtt 302 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.en.vtt 302 B
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.ar.vtt 302 B
Part 04-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.zh-CN.vtt 302 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.ja.vtt 302 B
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.pt-BR.vtt 302 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.ar.vtt 302 B
Part 16-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.ar.vtt 302 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.ar.vtt 302 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.ja.vtt 301 B
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.ar.vtt 301 B
Part 04-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.ja.vtt 301 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.es-ES.vtt 301 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.ja.vtt 300 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.ja.vtt 300 B
Part 16-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.ar.vtt 299 B
Part 16-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.pt-BR.vtt 299 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.th.vtt 299 B
Part 16-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.zh-CN.vtt 299 B
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.ar.vtt 298 B
Part 04-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.ja.vtt 298 B
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.en.vtt 298 B
Part 04-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.zh-CN.vtt 298 B
Part 16-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.ja.vtt 297 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.ja.vtt 297 B
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.ja.vtt 297 B
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.pt-BR.vtt 297 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.zh-CN.vtt 297 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.ja.vtt 296 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.en.vtt 296 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.ja.vtt 296 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.zh-CN.vtt 296 B
Part 16-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.zh-CN.vtt 295 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.zh-CN.vtt 294 B
Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.zh-CN.vtt 294 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.zh-CN.vtt 293 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.pt-BR.vtt 293 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.pt-BR.vtt 293 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.ja.vtt 293 B
Part 04-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.en.vtt 292 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.zh-CN.vtt 292 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.en.vtt 292 B
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.pt-BR.vtt 292 B
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.en.vtt 292 B
Part 16-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.zh-CN.vtt 291 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.it.vtt 291 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.pt-BR.vtt 291 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.zh-CN.vtt 291 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.hr.vtt 291 B
Part 16-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.ar.vtt 291 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.ja.vtt 291 B
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.zh-CN.vtt 291 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.pt-BR.vtt 291 B
Part 16-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.zh-CN.vtt 291 B
Part 16-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.en.vtt 290 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.en.vtt 290 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.hr.vtt 289 B
Part 16-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.en.vtt 289 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.it.vtt 289 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.pt-BR.vtt 289 B
Part 04-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.zh-CN.vtt 288 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.zh-CN.vtt 288 B
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.en.vtt 287 B
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.zh-CN.vtt 287 B
Part 16-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.zh-CN.vtt 287 B
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.zh-CN.vtt 286 B
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.en.vtt 286 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.ar.vtt 286 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.ja.vtt 285 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.en.vtt 285 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.zh-CN.vtt 285 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.pt-BR.vtt 285 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.ar.vtt 285 B
Part 16-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.en.vtt 285 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.pt-BR.vtt 284 B
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.ar.vtt 284 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.ar.vtt 283 B
Part 04-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.zh-CN.vtt 283 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.ar.vtt 283 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.zh-CN.vtt 283 B
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.ja.vtt 283 B
Part 04-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.zh-CN.vtt 282 B
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.en.vtt 282 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.en.vtt 282 B
Part 16-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.ar.vtt 282 B
Part 16-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.ar.vtt 282 B
Part 16-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.zh-CN.vtt 282 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.en.vtt 281 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.ja.vtt 281 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.pt-BR.vtt 281 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.es-ES.vtt 281 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.ar.vtt 281 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-UnkrtPPx9-c.ar.vtt 281 B
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.pt-BR.vtt 281 B
Part 04-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.zh-CN.vtt 280 B
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.ja.vtt 279 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.en.vtt 279 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.ar.vtt 279 B
Part 16-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.pt-BR.vtt 279 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.ar.vtt 278 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.ar.vtt 278 B
Part 08-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.zh-CN.vtt 277 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.en.vtt 277 B
Part 16-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.zh-CN.vtt 277 B
Part 04-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.zh-CN.vtt 277 B
Part 16-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.ja.vtt 277 B
Part 16-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.zh-CN.vtt 277 B
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.en.vtt 277 B
Part 16-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.pt-BR.vtt 276 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.pt-BR.vtt 276 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.zh-CN.vtt 275 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.pt-BR.vtt 274 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.ar.vtt 274 B
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.en.vtt 273 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.pt-BR.vtt 273 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.pt-BR.vtt 273 B
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.en.vtt 273 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price-MZyle39D5Ks.ar.vtt 273 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.es-ES.vtt 272 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.pt-BR.vtt 272 B
Part 16-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.pt-BR.vtt 272 B
Part 16-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.zh-CN.vtt 271 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.ar.vtt 271 B
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.pt-BR.vtt 271 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.pt-BR.vtt 270 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.pt-BR.vtt 269 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.en.vtt 268 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.zh-CN.vtt 268 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.th.vtt 267 B
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.zh-CN.vtt 266 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.ar.vtt 266 B
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.pt-BR.vtt 266 B
Part 16-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.en.vtt 265 B
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.ar.vtt 265 B
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.ar.vtt 265 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.ar.vtt 265 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.pt-BR.vtt 265 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.ar.vtt 265 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.ar.vtt 265 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.ar.vtt 265 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.zh-CN.vtt 264 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.pt-BR.vtt 264 B
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.pt-BR.vtt 264 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.ja.vtt 264 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.zh-CN.vtt 264 B
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.en.vtt 263 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.en.vtt 263 B
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.ar.vtt 263 B
Part 16-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.zh-CN.vtt 263 B
Part 16-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.zh-CN.vtt 263 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price--9CHGW25yMg.ja.vtt 263 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price--9CHGW25yMg.ar.vtt 262 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.ja.vtt 262 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.pt-BR.vtt 262 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.en.vtt 262 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.ja.vtt 261 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.pt-BR.vtt 261 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.ja.vtt 261 B
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.pt-BR.vtt 261 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.en.vtt 260 B
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.zh-CN.vtt 260 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.es-ES.vtt 260 B
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.pt-BR.vtt 260 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.ja.vtt 260 B
Part 16-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.en.vtt 260 B
Part 16-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.zh-CN.vtt 259 B
Part 16-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.ar.vtt 258 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.es-ES.vtt 258 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.es-ES.vtt 257 B
Part 04-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.zh-CN.vtt 257 B
Part 04-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.zh-CN.vtt 256 B
Part 16-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.pt-BR.vtt 256 B
Part 16-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.ja.vtt 256 B
Part 16-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.zh-CN.vtt 256 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.ja.vtt 256 B
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.ar.vtt 256 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.en.vtt 256 B
Part 16-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.en.vtt 256 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.zh-CN.vtt 256 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.en.vtt 256 B
Part 16-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.zh-CN.vtt 255 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.pt-BR.vtt 255 B
Part 16-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.zh-CN.vtt 255 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.ja.vtt 255 B
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.en.vtt 254 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.ja.vtt 254 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.ar.vtt 254 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.pt-BR.vtt 254 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-W96zaGEma7o.ja.vtt 254 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.pt-BR.vtt 253 B
Part 16-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.zh-CN.vtt 253 B
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.en.vtt 252 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.es-ES.vtt 252 B
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.hr.vtt 252 B
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.ar.vtt 252 B
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.en.vtt 252 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.en.vtt 252 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.th.vtt 252 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-UnkrtPPx9-c.ja.vtt 251 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.es-ES.vtt 251 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price-MZyle39D5Ks.ja.vtt 251 B
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.ar.vtt 251 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.zh-CN.vtt 251 B
Part 04-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.zh-CN.vtt 251 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.ar.vtt 250 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.zh-CN.vtt 250 B
Part 16-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.ar.vtt 250 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-W96zaGEma7o.pt-BR.vtt 250 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.en.vtt 250 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.pt-BR.vtt 249 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.pt-BR.vtt 249 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.pt-BR.vtt 249 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.pt-BR.vtt 249 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.pt-BR.vtt 249 B
Part 16-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.zh-CN.vtt 249 B
Part 04-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.ar.vtt 248 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.zh-CN.vtt 248 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.zh-CN.vtt 248 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.en.vtt 248 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.it.vtt 248 B
Part 16-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.pt-BR.vtt 248 B
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.pt-BR.vtt 248 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.ja.vtt 248 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.ar.vtt 248 B
Part 16-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.en.vtt 247 B
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.ja.vtt 247 B
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.pt-BR.vtt 247 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.ja.vtt 247 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.en.vtt 247 B
Part 16-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.en.vtt 246 B
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.en.vtt 246 B
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.ja.vtt 246 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.pt-BR.vtt 246 B
Part 16-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.zh-CN.vtt 245 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.en.vtt 245 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.zh-CN.vtt 244 B
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.ar.vtt 244 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.en.vtt 244 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.zh-CN.vtt 244 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.th.vtt 244 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.es-ES.vtt 243 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.ja.vtt 243 B
Part 16-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.zh-CN.vtt 243 B
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.ja.vtt 243 B
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.es-ES.vtt 242 B
Part 16-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.ar.vtt 241 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.ja.vtt 241 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.zh-CN.vtt 241 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.zh-CN.vtt 241 B
Part 04-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.zh-CN.vtt 241 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.en.vtt 241 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.th.vtt 240 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.th.vtt 240 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.pt-BR.vtt 240 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.it.vtt 240 B
Part 16-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.pt-BR.vtt 240 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.en.vtt 240 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.pt-BR.vtt 239 B
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.en.vtt 239 B
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.it.vtt 239 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.es-ES.vtt 239 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.hr.vtt 238 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.es-ES.vtt 238 B
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.ar.vtt 238 B
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.en.vtt 238 B
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.en.vtt 238 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.ar.vtt 238 B
Part 04-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.ja.vtt 237 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.pt-BR.vtt 237 B
Part 16-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.zh-CN.vtt 236 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.es-ES.vtt 236 B
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.ja.vtt 236 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.ar.vtt 234 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.es-ES.vtt 234 B
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.ar.vtt 234 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.it.vtt 234 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.es-ES.vtt 234 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.es-ES.vtt 233 B
Part 16-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.zh-CN.vtt 233 B
Part 16-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.pt-BR.vtt 233 B
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.zh-CN.vtt 232 B
Part 16-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.zh-CN.vtt 232 B
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.pt-BR.vtt 232 B
Part 16-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.en.vtt 232 B
Part 16-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.ja.vtt 232 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.en.vtt 231 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.es-ES.vtt 231 B
Part 16-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.ar.vtt 231 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.it.vtt 231 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price-MZyle39D5Ks.pt-BR.vtt 230 B
Part 16-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.pt-BR.vtt 230 B
Part 16-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.en.vtt 229 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.th.vtt 228 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.zh-CN.vtt 228 B
Part 16-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.pt-BR.vtt 228 B
Part 04-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.zh-CN.vtt 228 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.es-ES.vtt 227 B
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.zh-CN.vtt 226 B
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.pt-BR.vtt 226 B
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.pt-BR.vtt 226 B
Part 16-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.ar.vtt 226 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.zh-CN.vtt 226 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.ja.vtt 226 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.ja.vtt 225 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.pt-BR.vtt 225 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.ar.vtt 225 B
Part 04-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.zh-CN.vtt 225 B
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.pt-BR.vtt 224 B
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.en.vtt 224 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.pt-BR.vtt 223 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.pt-BR.vtt 223 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.ar.vtt 222 B
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.pt-BR.vtt 222 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.ar.vtt 222 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.ar.vtt 222 B
Part 16-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.en.vtt 222 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.en.vtt 222 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.zh-CN.vtt 222 B
Part 16-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.zh-CN.vtt 222 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price--9CHGW25yMg.pt-BR.vtt 221 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.en.vtt 221 B
Part 16-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.en.vtt 221 B
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.es-ES.vtt 221 B
Part 16-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.zh-CN.vtt 220 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-W96zaGEma7o.en.vtt 220 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price--9CHGW25yMg.en.vtt 220 B
Part 16-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.en.vtt 220 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.ja.vtt 220 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.en.vtt 219 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.en.vtt 219 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.en.vtt 219 B
Part 16-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.pt-BR.vtt 219 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.en.vtt 219 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.zh-CN.vtt 219 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.pt-BR.vtt 219 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-UnkrtPPx9-c.pt-BR.vtt 219 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.ja.vtt 219 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.es-ES.vtt 219 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.zh-CN.vtt 218 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.ar.vtt 218 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.ar.vtt 218 B
Part 04-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.ar.vtt 218 B
Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.ar.vtt 218 B
Part 04-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.pt-BR.vtt 218 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.es-ES.vtt 217 B
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.pt-BR.vtt 217 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.ja.vtt 217 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.en.vtt 217 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.en.vtt 216 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.hr.vtt 216 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.pt-BR.vtt 216 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.ja.vtt 216 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.en.vtt 216 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.zh-CN.vtt 216 B
Part 04-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.zh-CN.vtt 215 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.pt-BR.vtt 215 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.pt-PT.vtt 215 B
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.en.vtt 214 B
Part 16-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.en.vtt 214 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price-MZyle39D5Ks.en.vtt 214 B
Part 04-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.en.vtt 214 B
Part 04-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.zh-CN.vtt 214 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.en.vtt 214 B
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.en.vtt 213 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.en.vtt 213 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.zh-CN.vtt 213 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.hr.vtt 213 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.it.vtt 213 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/18. Color and Price--9CHGW25yMg.zh-CN.vtt 212 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.ja.vtt 212 B
Part 04-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.zh-CN.vtt 212 B
Part 07-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.zh-CN.vtt 212 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.it.vtt 212 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.pt-BR.vtt 212 B
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.en.vtt 212 B
Part 04-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.zh-CN.vtt 212 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.ar.vtt 211 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.ja.vtt 211 B
Part 16-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.zh-CN.vtt 211 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.ar.vtt 210 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.it.vtt 210 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.es-ES.vtt 210 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.en.vtt 210 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.en.vtt 210 B
Part 04-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.zh-CN.vtt 210 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.zh-CN.vtt 209 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.hr.vtt 209 B
Part 04-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.pt-BR.vtt 209 B
Part 16-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.zh-CN.vtt 208 B
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.en.vtt 208 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.ar.vtt 208 B
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.en.vtt 207 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-UnkrtPPx9-c.en.vtt 207 B
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.zh-CN.vtt 207 B
Part 16-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.en.vtt 207 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.ar.vtt 207 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.pt-BR.vtt 207 B
Part 16-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.zh-CN.vtt 207 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.zh-CN.vtt 207 B
Part 16-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.en.vtt 207 B
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.pt-BR.vtt 206 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/03. Scatterplot Review-W96zaGEma7o.zh-CN.vtt 206 B
Part 16-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.zh-CN.vtt 206 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.ja.vtt 205 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.it.vtt 205 B
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.en.vtt 205 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.th.vtt 205 B
Part 16-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.pt-BR.vtt 205 B
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.ja.vtt 205 B
Part 16-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.pt-BR.vtt 204 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.zh-CN.vtt 204 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.zh-CN.vtt 204 B
Part 16-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.ar.vtt 204 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.th.vtt 204 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.ar.vtt 204 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.hr.vtt 204 B
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.zh-CN.vtt 204 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.pt-BR.vtt 203 B
Part 16-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-th34aboBOO0.ar.vtt 203 B
Part 04-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.pt-BR.vtt 203 B
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.en.vtt 203 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.en.vtt 203 B
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.pt-BR.vtt 202 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.ja.vtt 202 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.ar.vtt 202 B
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.pt-BR.vtt 201 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.pt-BR.vtt 201 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/16. Cut and Price-MZyle39D5Ks.zh-CN.vtt 201 B
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.en.vtt 201 B
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.en.vtt 201 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.ja.vtt 201 B
Part 04-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.ja.vtt 200 B
Part 16-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.zh-CN.vtt 200 B
Part 16-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.en.vtt 199 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.ja.vtt 199 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.pt-BR.vtt 199 B
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.ja.vtt 199 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.zh-CN.vtt 198 B
Part 04-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.ja.vtt 198 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.en.vtt 198 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.hr.vtt 197 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.zh-CN.vtt 197 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.ja.vtt 197 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.ar.vtt 196 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.en.vtt 196 B
Part 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.ar.vtt 196 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.zh-CN.vtt 196 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.ja.vtt 196 B
Part 16-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.pt-BR.vtt 196 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.en.vtt 194 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.ja.vtt 194 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.ja.vtt 194 B
Part 16-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.zh-CN.vtt 194 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.en.vtt 193 B
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.ja.vtt 193 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.es-ES.vtt 192 B
Part 04-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.zh-CN.vtt 192 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.ar.vtt 191 B
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.zh-CN.vtt 191 B
Part 16-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.zh-CN.vtt 191 B
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.ja.vtt 190 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.en.vtt 190 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.ar.vtt 190 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.ja.vtt 190 B
Part 16-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.zh-CN.vtt 190 B
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.zh-CN.vtt 189 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.zh-Hans.vtt 189 B
Part 16-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.pt-BR.vtt 189 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/14. Clarity and Price-UnkrtPPx9-c.zh-CN.vtt 188 B
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.pt-BR.vtt 188 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.pt-BR.vtt 188 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.ar.vtt 188 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.pt-BR.vtt 188 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.zh-CN.vtt 187 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.ja.vtt 187 B
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.ar.vtt 187 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.ja.vtt 187 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.it.vtt 187 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.ar.vtt 187 B
Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.zh-CN.vtt 187 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.en.vtt 186 B
Part 04-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.pt-BR.vtt 186 B
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.pt-BR.vtt 186 B
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.en.vtt 186 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.zh-CN.vtt 186 B
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.pt-BR.vtt 185 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.es-ES.vtt 185 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.zh-CN.vtt 185 B
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.en.vtt 185 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.ar.vtt 184 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.pt-BR.vtt 184 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.en.vtt 184 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.ar.vtt 184 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.ja.vtt 184 B
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.zh-CN.vtt 183 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.pt-BR.vtt 183 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.en.vtt 182 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.zh-CN.vtt 182 B
Part 04-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.en.vtt 182 B
Part 16-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.zh-CN.vtt 182 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.ja.vtt 181 B
Part 16-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.en.vtt 181 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.pt-BR.vtt 181 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.ja.vtt 180 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.en.vtt 180 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.zh-CN.vtt 180 B
Part 16-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.pt-BR.vtt 180 B
Part 04-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.zh-CN.vtt 180 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.zh-CN.vtt 180 B
Part 04-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.en.vtt 178 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.en.vtt 178 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.it.vtt 178 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.th.vtt 178 B
Part 16-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.pt-BR.vtt 177 B
Part 04-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.zh-CN.vtt 177 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.pt-BR.vtt 177 B
Part 16-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.zh-CN.vtt 177 B
Part 16-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.pt-BR.vtt 177 B
Part 04-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.pt-BR.vtt 177 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.th.vtt 177 B
Part 16-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.zh-CN.vtt 176 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.ar.vtt 176 B
Part 16-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-dk3FxGVdP7Q.ar.vtt 176 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.ja.vtt 176 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.ja.vtt 175 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.ar.vtt 175 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.es-ES.vtt 174 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.es-ES.vtt 174 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.en.vtt 174 B
Part 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.en.vtt 174 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.it.vtt 174 B
Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.pt-BR.vtt 173 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.pt-BR.vtt 173 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.pt-BR.vtt 173 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.pt-BR.vtt 173 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.it.vtt 173 B
Part 16-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.zh-CN.vtt 172 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.it.vtt 171 B
Part 16-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.pt-BR.vtt 171 B
Part 16-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.ar.vtt 171 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.pt-BR.vtt 171 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.it.vtt 171 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.es-ES.vtt 170 B
Part 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.pt-BR.vtt 170 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.pt-BR.vtt 170 B
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.pt-BR.vtt 170 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.pt-BR.vtt 169 B
Part 16-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.zh-CN.vtt 169 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.pt-BR.vtt 169 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.en.vtt 169 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.pt-BR.vtt 168 B
Part 16-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.ar.vtt 168 B
Part 04-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.pt-BR.vtt 167 B
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.en.vtt 167 B
Part 16-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.en.vtt 167 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.pt-BR.vtt 167 B
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.ar.vtt 167 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.en.vtt 167 B
Part 16-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.zh-CN.vtt 167 B
Part 16-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.zh-CN.vtt 166 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.ar.vtt 166 B
Part 16-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.zh-CN.vtt 166 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.zh-CN.vtt 166 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.es-ES.vtt 166 B
Part 16-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.zh-CN.vtt 166 B
Part 16-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.ja.vtt 165 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.es-ES.vtt 165 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.en.vtt 165 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.pt-BR.vtt 165 B
Part 16-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.zh-CN.vtt 165 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.th.vtt 164 B
Part 16-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.en.vtt 164 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.pt-BR.vtt 164 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.it.vtt 164 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.pt-BR.vtt 164 B
Part 16-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.pt-BR.vtt 164 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.zh-CN.vtt 164 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.ar.vtt 163 B
Part 16-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.en.vtt 163 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.zh-CN.vtt 163 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.hr.vtt 163 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.pt-BR.vtt 162 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.en.vtt 161 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.ar.vtt 161 B
Part 04-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.en.vtt 161 B
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.pt-BR.vtt 160 B
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.pt-BR.vtt 160 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.zh-CN.vtt 160 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.es-ES.vtt 160 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.th.vtt 160 B
Part 04-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.zh-CN.vtt 160 B
Part 16-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.pt-BR.vtt 159 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.ja.vtt 159 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.pt-BR.vtt 159 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.zh-CN.vtt 158 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.zh-CN.vtt 158 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.pt-BR.vtt 158 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.ar.vtt 158 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.zh-CN.vtt 157 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.es-ES.vtt 157 B
Part 16-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.ar.vtt 157 B
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.ja.vtt 157 B
Part 16-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.zh-CN.vtt 157 B
Part 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.zh-CN.vtt 157 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.pt-BR.vtt 157 B
Part 04-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.hr.vtt 157 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.ja.vtt 156 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.es-ES.vtt 155 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.en.vtt 155 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.en.vtt 155 B
Part 04-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.pt-BR.vtt 155 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.pt-BR.vtt 155 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.hr.vtt 155 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.ja.vtt 155 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.zh-CN.vtt 155 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.ja.vtt 154 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.en.vtt 153 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.ar.vtt 153 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.zh-CN.vtt 153 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.ja.vtt 152 B
Part 04-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.zh-CN.vtt 152 B
Part 16-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.zh-CN.vtt 152 B
Part 04-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.en.vtt 152 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.ar.vtt 152 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.th.vtt 152 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.it.vtt 151 B
Part 04-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.zh-CN.vtt 150 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.zh-CN.vtt 150 B
Part 04-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.zh-CN.vtt 150 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.pt-BR.vtt 149 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.zh-CN.vtt 149 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.zh-CN.vtt 149 B
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.ja.vtt 149 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.hr.vtt 149 B
Part 04-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.ja.vtt 149 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.pt-BR.vtt 149 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.en.vtt 148 B
Part 04-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.en.vtt 147 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.pt-BR.vtt 146 B
Part 04-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.en.vtt 146 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.hr.vtt 144 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.ar.vtt 144 B
Part 16-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.pt-BR.vtt 143 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.en.vtt 143 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.es-ES.vtt 143 B
Part 04-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.zh-CN.vtt 142 B
Part 04-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.en.vtt 142 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.es-ES.vtt 142 B
Part 04-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.en.vtt 142 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.ja.vtt 142 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.zh-CN.vtt 142 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.en.vtt 142 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.es-ES.vtt 141 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.ar.vtt 141 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.es-ES.vtt 141 B
Part 04-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.ja.vtt 141 B
Part 16-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-th34aboBOO0.pt-BR.vtt 141 B
Part 16-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.en.vtt 141 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.ja.vtt 141 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.es-ES.vtt 140 B
Part 16-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.en.vtt 140 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.en.vtt 140 B
Part 16-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.ar.vtt 140 B
Part 16-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-th34aboBOO0.en.vtt 139 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.ja.vtt 139 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.es-ES.vtt 138 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.en.vtt 138 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.it.vtt 138 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.ja.vtt 138 B
Part 16-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.en.vtt 138 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.ja.vtt 137 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-dyShKWpTo-c.en.vtt 137 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.th.vtt 137 B
Part 04-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-dyShKWpTo-c.en.vtt 137 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.en.vtt 136 B
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.zh-CN.vtt 136 B
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.ar.vtt 136 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.th.vtt 135 B
Part 16-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-dk3FxGVdP7Q.pt-BR.vtt 134 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.ja.vtt 134 B
Part 16-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-dyShKWpTo-c.pt-BR.vtt 133 B
Part 04-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-dyShKWpTo-c.pt-BR.vtt 133 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.ja.vtt 132 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.ar.vtt 132 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.ja.vtt 131 B
Part 16-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.ja.vtt 131 B
Part 16-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.en.vtt 131 B
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.pt-BR.vtt 130 B
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.es-ES.vtt 130 B
Part 16-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-dk3FxGVdP7Q.en.vtt 130 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.en.vtt 130 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.th.vtt 130 B
Part 16-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.en.vtt 130 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.it.vtt 129 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.en.vtt 129 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.ar.vtt 129 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.es-ES.vtt 129 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.zh-CN.vtt 129 B
Part 16-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.en.vtt 128 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.en.vtt 128 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.it.vtt 127 B
Part 04-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.zh-CN.vtt 127 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.zh-CN.vtt 126 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.ja.vtt 126 B
Part 04-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.zh-CN.vtt 126 B
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.ar.vtt 126 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.ar.vtt 126 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.es-ES.vtt 125 B
Part 16-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.zh-CN.vtt 125 B
Part 16-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.zh-CN.vtt 125 B
Part 16-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.zh-CN.vtt 125 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.pt-BR.vtt 125 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.es-ES.vtt 125 B
Part 16-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.pt-BR.vtt 124 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.ja.vtt 123 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.ja.vtt 123 B
Part 04-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.zh-CN.vtt 123 B
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.ar.vtt 123 B
Part 04-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.zh-CN.vtt 123 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.pt-BR.vtt 123 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.pt-BR.vtt 122 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.ar.vtt 122 B
Part 16-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.pt-BR.vtt 122 B
Part 04-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.en.vtt 122 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.ja.vtt 122 B
Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.ar.vtt 122 B
Part 16-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.pt-BR.vtt 121 B
Part 16-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-kNxZwfXwvuk.ar.vtt 121 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.en.vtt 120 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.es-ES.vtt 120 B
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.ja.vtt 119 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.zh-Hans.vtt 119 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.en.vtt 119 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.en.vtt 118 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.ja.vtt 118 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.ar.vtt 118 B
Part 16-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.ar.vtt 118 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.es-ES.vtt 118 B
Part 04-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.zh-CN.vtt 118 B
Part 04-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.zh-CN.vtt 117 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.ja.vtt 116 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.zh-CN.vtt 116 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.zh-CN.vtt 115 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.zh-CN.vtt 113 B
Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.zh-CN.vtt 113 B
Part 04-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.zh-CN.vtt 113 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.ja.vtt 113 B
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.pt-BR.vtt 111 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.zh-CN.vtt 111 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.zh-CN.vtt 110 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.ar.vtt 110 B
Part 16-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.ar.vtt 110 B
Part 04-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.en.vtt 110 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.ja.vtt 110 B
Part 16-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.pt-BR.vtt 110 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.es-ES.vtt 109 B
Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.en.vtt 109 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.es-ES.vtt 109 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.en.vtt 109 B
Part 16-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.pt-BR.vtt 109 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.pt-BR.vtt 108 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.zh-CN.vtt 108 B
Part 16-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.en.vtt 108 B
Part 16-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.en.vtt 108 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.ar.vtt 108 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.th.vtt 108 B
Part 04-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.pt-BR.vtt 108 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.es-ES.vtt 108 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.es-ES.vtt 107 B
Part 16-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.ja.vtt 107 B
Part 16-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.zh-CN.vtt 107 B
Part 16-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.en.vtt 107 B
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Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.ja.vtt 106 B
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Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.zh-CN.vtt 101 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.es-ES.vtt 101 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.zh-Hans.vtt 101 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.pt-BR.vtt 100 B
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.ja.vtt 100 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.pt-BR.vtt 99 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.zh-CN.vtt 99 B
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.ar.vtt 99 B
Part 04-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.pt-BR.vtt 99 B
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.ar.vtt 99 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.ar.vtt 98 B
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.zh-Hans.vtt 98 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.zh-CN.vtt 98 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.ja.vtt 97 B
Part 04-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.en.vtt 97 B
Part 16-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-kNxZwfXwvuk.pt-BR.vtt 97 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.ar.vtt 96 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.it.vtt 96 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.es-ES.vtt 95 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.hr.vtt 95 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.ar.vtt 95 B
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.es-ES.vtt 95 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.en.vtt 95 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.en.vtt 95 B
Part 04-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.it.vtt 94 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.ar.vtt 94 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.ja.vtt 94 B
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.zh-CN.vtt 94 B
Part 04-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.pt-BR.vtt 94 B
Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.ar.vtt 93 B
Part 16-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-kNxZwfXwvuk.en.vtt 92 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.ar.vtt 92 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.pt-BR.vtt 92 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.ja.vtt 91 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.pt-BR.vtt 91 B
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.pt-BR.vtt 90 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.ar.vtt 90 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.zh-CN.vtt 90 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.en.vtt 90 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.en.vtt 90 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.it.vtt 90 B
Part 04-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.zh-CN.vtt 90 B
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Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.pt-PT.vtt 89 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.it.vtt 89 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.pt-BR.vtt 89 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.ja.vtt 89 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.it.vtt 89 B
Part 16-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.zh-CN.vtt 89 B
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.ja.vtt 89 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.pt-BR.vtt 89 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.ja.vtt 88 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.ja.vtt 88 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.it.vtt 88 B
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.en.vtt 88 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.it.vtt 87 B
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.hr.vtt 87 B
Part 04-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.zh-CN.vtt 87 B
Part 16-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.en.vtt 86 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.hr.vtt 86 B
Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.pt-BR.vtt 86 B
Part 16-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.en.vtt 86 B
Part 04-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.en.vtt 86 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.en.vtt 86 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.zh-Hans.vtt 85 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.hr.vtt 85 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.hr.vtt 85 B
Part 04-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.zh-CN.vtt 84 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.zh-CN.vtt 84 B
Part 04-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.hr.vtt 83 B
Part 04-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.zh-CN.vtt 83 B
Part 04-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.tr.vtt 81 B
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