[DesireCourse.Com] Udemy - Data Science and Machine Learning Bootcamp with R

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  • 18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.mp4 54.46 MB
    19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.mp4 48.51 MB
    21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.mp4 47.76 MB
    23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.mp4 47.41 MB
    14. Data Manipulation with R/8. Guide to Using Tidyr.mp4 47.11 MB
    20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.mp4 46.95 MB
    33. Machine Learning with R - Neural Nets/2. Neural Nets with R.mp4 46.26 MB
    20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.mp4 45.94 MB
    15. Data Visualization with R/2. Histograms.mp4 45.61 MB
    1. Course Introduction/4.1 R-Course-HTML-Notes.zip.zip 45.6 MB
    6. Development Environment Overview/2.1 R-Course-HTML-Notes.zip.zip 45.6 MB
    22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.mp4 40.93 MB
    24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.mp4 40.42 MB
    22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.mp4 39.59 MB
    15. Data Visualization with R/3. Scatterplots.mp4 37.54 MB
    12. R Programming Basics/10. Functions Training Exercise - Solutions.mp4 36.76 MB
    32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.mp4 35.68 MB
    12. R Programming Basics/8. Functions.mp4 35.11 MB
    18. Capstone Data Project/1. Introduction to Capstone Project.mp4 34.96 MB
    9. R Data Frames/5. Overview of Data Frame Operations - Part 2.mp4 34.14 MB
    21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.mp4 33.67 MB
    17. Interactive Visualizations with Plotly/1. Overview of Plotly and Interactive Visualizations.mp4 33.53 MB
    27. Machine Learning Project - Decision Trees and Random Forests/2. Tree Methods Project Solutions - Part 1.mp4 33.43 MB
    28. Machine Learning with R - Support Vector Machines/2. Support Vector Machines with R.mp4 32.98 MB
    31. Machine Learning Project - K-means Clustering/2. K Means Clustering Project - Solutions Walkthrough.mp4 32.97 MB
    23. Machine Learning Project - Logistic Regression/3. Logistic Regression Project Solutions - Part 2.mp4 32.84 MB
    16. Data Visualization Project/2. Data Visualization Project - Solutions Walkthrough - Part 1.mp4 32.61 MB
    23. Machine Learning Project - Logistic Regression/4. Logistic Regression Project - Solutions Part 3.mp4 32.17 MB
    16. Data Visualization Project/3. Data Visualization Project Solutions Walkthrough - Part 2.mp4 32.13 MB
    9. R Data Frames/4. Overview of Data Frame Operations - Part 1.mp4 30.45 MB
    9. R Data Frames/7. Data Frame Training Exercises - Solutions Walkthrough.mp4 28.97 MB
    26. Machine Learning with R - Decision Trees and Random Forests/2. Decision Trees and Random Forests with R.mp4 28.82 MB
    6. Development Environment Overview/3. Guide to RStudio.mp4 28.33 MB
    13. Advanced R Programming/3. Apply.mp4 28.07 MB
    21. Machine Learning Project - Linear Regression/3. ML - Linear Regression Project - Solutions Part 2.mp4 26.07 MB
    15. Data Visualization with R/10. ggplot2 Exercise Solutions.mp4 26.03 MB
    12. R Programming Basics/3. if, else, and else if Statements.mp4 25.93 MB
    6. Development Environment Overview/2. Course Notes.mp4 25.73 MB
    11. Data Input and Output with R/4. SQL with R.mp4 25.48 MB
    25. Machine Learning Project - K Nearest Neighbors/2. K Nearest Neighbors Project Solutions.mp4 25.18 MB
    14. Data Manipulation with R/2. Guide to Using Dplyr.mp4 25.14 MB
    8. R Matrices/8. Matrix Training Exercises - Solutions Walkthrough.mp4 24.63 MB
    11. Data Input and Output with R/3. Excel Files with R.mp4 24.17 MB
    29. Machine Learning Project - Support Vector Machines/2. Support Vector Machines Project - Solutions Part 1.mp4 24.13 MB
    15. Data Visualization with R/7. Coordinates and Faceting.mp4 24.08 MB
    13. Advanced R Programming/6. Dates and Timestamps.mp4 24.02 MB
    12. R Programming Basics/7. For Loops.mp4 23.11 MB
    20. Machine Learning with R - Linear Regression/4. Linear Regression with R - Part 3.mp4 22.79 MB
    12. R Programming Basics/5. Conditional Statements Training Exercise - Solutions Walkthrough.mp4 21.08 MB
    29. Machine Learning Project - Support Vector Machines/3. Support Vector Machines Project - Solutions Part 2.mp4 21.04 MB
    4. Mac OS Installation Set-Up/1. Mac OS Installation Procedure.mp4 20.84 MB
    34. Machine Learning Project - Neural Nets/2. Neural Nets Project - Solutions.mp4 20.61 MB
    14. Data Manipulation with R/3. Guide to Using Dplyr - Part 2.mp4 20.53 MB
    15. Data Visualization with R/6. 2 Variable Plotting.mp4 20.42 MB
    22. Machine Learning with R - Logistic Regression/1. Introduction to Logistic Regression.mp4 19.84 MB
    10. R Lists/1. List Basics.mp4 19.58 MB
    30. Machine Learning with R - K-means Clustering/2. K Means Clustering with R.mp4 19.21 MB
    8. R Matrices/2. Creating a Matrix.mp4 18.64 MB
    9. R Data Frames/2. Data Frame Basics.mp4 18.22 MB
    13. Advanced R Programming/2. Built-in R Features.mp4 18.03 MB
    3. Windows Installation Set-Up/1. Windows Installation Procedure.mp4 17.76 MB
    11. Data Input and Output with R/5. Web Scraping with R.mp4 17.4 MB
    9. R Data Frames/3. Data Frame Indexing and Selection.mp4 16.82 MB
    15. Data Visualization with R/4. Barplots.mp4 16.79 MB
    7. Introduction to R Basics/8. Vector Indexing and Slicing.mp4 16.06 MB
    8. R Matrices/6. Factor and Categorical Matrices.mp4 14.84 MB
    12. R Programming Basics/2. Logical Operators.mp4 14.52 MB
    15. Data Visualization with R/5. Boxplots.mp4 14.09 MB
    14. Data Manipulation with R/7. Dplyr Training Exercise - Solutions Walkthrough.vtt 13.81 MB
    14. Data Manipulation with R/7. Dplyr Training Exercise - Solutions Walkthrough.mp4 13.79 MB
    14. Data Manipulation with R/4. Pipe Operator.mp4 13.77 MB
    7. Introduction to R Basics/5. Vector Basics.mp4 13.67 MB
    7. Introduction to R Basics/11. R Basics Training Exercise - Solutions Walkthrough.mp4 12.78 MB
    1. Course Introduction/1. Introduction to Course.mp4 12.43 MB
    11. Data Input and Output with R/2. CSV Files with R.mp4 12.2 MB
    12. R Programming Basics/6. While Loops.mp4 12 MB
    15. Data Visualization with R/1. Overview of ggplot2.mp4 11.99 MB
    8. R Matrices/5. Matrix Selection and Indexing.mp4 11.78 MB
    25. Machine Learning Project - K Nearest Neighbors/1. Introduction K Nearest Neighbors Project.mp4 11.71 MB
    16. Data Visualization Project/1. Data Visualization Project.mp4 11.61 MB
    26. Machine Learning with R - Decision Trees and Random Forests/1. Introduction to Tree Methods.mp4 11.25 MB
    15. Data Visualization with R/8. Themes.mp4 11.24 MB
    33. Machine Learning with R - Neural Nets/1. Introduction to Neural Nets.mp4 11.22 MB
    8. R Matrices/4. Matrix Operations.mp4 10.78 MB
    7. Introduction to R Basics/7. Comparison Operators.mp4 10.7 MB
    32. Machine Learning with R - Natural Language Processing/2. Natural Language Processing with R - Part 1.mp4 10.44 MB
    20. Machine Learning with R - Linear Regression/1. Introduction to Linear Regression.mp4 10.18 MB
    23. Machine Learning Project - Logistic Regression/1. Introduction to Logistic Regression Project.mp4 10.1 MB
    13. Advanced R Programming/5. Regular Expressions.mp4 9.72 MB
    29. Machine Learning Project - Support Vector Machines/1. Introduction to SVM Project.mp4 9.32 MB
    13. Advanced R Programming/4. Math Functions with R.mp4 9.25 MB
    27. Machine Learning Project - Decision Trees and Random Forests/3. Tree Methods Project Solutions - Part 2.mp4 9.15 MB
    7. Introduction to R Basics/4. R Basic Data Types.mp4 9.06 MB
    7. Introduction to R Basics/3. Variables.mp4 8.94 MB
    30. Machine Learning with R - K-means Clustering/1. Introduction to K-Means Clustering.mp4 8.57 MB
    24. Machine Learning with R - K Nearest Neighbors/1. Introduction to K Nearest Neighbors.mp4 8.51 MB
    27. Machine Learning Project - Decision Trees and Random Forests/1. Introduction to Decision Trees and Random Forests Project.mp4 8.44 MB
    34. Machine Learning Project - Neural Nets/1. Introduction to Neural Nets Project.mp4 8.39 MB
    28. Machine Learning with R - Support Vector Machines/1. Introduction to Support Vector Machines.mp4 7.97 MB
    8. R Matrices/3. Matrix Arithmetic.mp4 7.78 MB
    7. Introduction to R Basics/2. Arithmetic in R.mp4 7.7 MB
    32. Machine Learning with R - Natural Language Processing/1. Introduction to Natural Language Processing.mp4 7.58 MB
    7. Introduction to R Basics/6. Vector Operations.mp4 7.55 MB
    31. Machine Learning Project - K-means Clustering/1. Introduction to K Means Clustering Project.mp4 7.22 MB
    1. Course Introduction/3. What is Data Science.mp4 7.01 MB
    15. Data Visualization with R/9. ggplot2 Exercises.mp4 6.7 MB
    12. R Programming Basics/9. Functions Training Exercise.mp4 6.69 MB
    1. Course Introduction/2. Course Curriculum.mp4 5.71 MB
    7. Introduction to R Basics/9. Getting Help with R and RStudio.mp4 5.64 MB
    7. Introduction to R Basics/1. Introduction to R Basics.mp4 5.63 MB
    7. Introduction to R Basics/10. R Basics Training Exercise.mp4 5.37 MB
    9. R Data Frames/6. Data Frame Training Exercise.mp4 4.27 MB
    12. R Programming Basics/4. Conditional Statements Training Exercise.mp4 3.47 MB
    8. R Matrices/7. Matrix Training Exercise.mp4 3.24 MB
    19. Introduction to Machine Learning with R/2.1 Machine Learning Slides.zip.zip 2.87 MB
    14. Data Manipulation with R/6. Dplyr Training Exercise.mp4 2.69 MB
    12. R Programming Basics/1. Introduction to Programming Basics.mp4 1.72 MB
    13. Advanced R Programming/1. Introduction to Advanced R Programming.mp4 1.61 MB
    8. R Matrices/1. Introduction to R Matrices.mp4 1.46 MB
    9. R Data Frames/1. Introduction to R Data Frames.mp4 1.36 MB
    14. Data Manipulation with R/1. Data Manipulation Overview.mp4 1.17 MB
    6. Development Environment Overview/1. Development Environment Overview.mp4 870.33 KB
    11. Data Input and Output with R/1. Introduction to Data Input and Output with R.mp4 869.69 KB
    33. Machine Learning with R - Neural Nets/2. Neural Nets with R.vtt 28.09 KB
    20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.vtt 26.78 KB
    18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.vtt 26.24 KB
    21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.vtt 26.04 KB
    12. R Programming Basics/10. Functions Training Exercise - Solutions.vtt 25.38 KB
    20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.vtt 25.15 KB
    22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.vtt 24.9 KB
    14. Data Manipulation with R/8. Guide to Using Tidyr.vtt 24.88 KB
    15. Data Visualization with R/2. Histograms.vtt 24.81 KB
    23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.vtt 24.74 KB
    19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.vtt 24.3 KB
    9. R Data Frames/5. Overview of Data Frame Operations - Part 2.vtt 23.78 KB
    12. R Programming Basics/8. Functions.vtt 23.29 KB
    24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.vtt 22.53 KB
    22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.vtt 22.18 KB
    9. R Data Frames/4. Overview of Data Frame Operations - Part 1.vtt 21.76 KB
    15. Data Visualization with R/3. Scatterplots.vtt 21.26 KB
    31. Machine Learning Project - K-means Clustering/2. K Means Clustering Project - Solutions Walkthrough.vtt 20.9 KB
    27. Machine Learning Project - Decision Trees and Random Forests/2. Tree Methods Project Solutions - Part 1.vtt 20.29 KB
    23. Machine Learning Project - Logistic Regression/3. Logistic Regression Project Solutions - Part 2.vtt 19.38 KB
    28. Machine Learning with R - Support Vector Machines/2. Support Vector Machines with R.vtt 18.55 KB
    9. R Data Frames/7. Data Frame Training Exercises - Solutions Walkthrough.vtt 18.45 KB
    32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.vtt 18.08 KB
    13. Advanced R Programming/3. Apply.vtt 17.93 KB
    12. R Programming Basics/3. if, else, and else if Statements.vtt 17.69 KB
    23. Machine Learning Project - Logistic Regression/4. Logistic Regression Project - Solutions Part 3.vtt 17.16 KB
    15. Data Visualization with R/10. ggplot2 Exercise Solutions.vtt 17.12 KB
    6. Development Environment Overview/3. Guide to RStudio.vtt 17.03 KB
    8. R Matrices/8. Matrix Training Exercises - Solutions Walkthrough.vtt 17.02 KB
    12. R Programming Basics/7. For Loops.vtt 16.02 KB
    14. Data Manipulation with R/2. Guide to Using Dplyr.vtt 15.92 KB
    11. Data Input and Output with R/3. Excel Files with R.vtt 15.71 KB
    12. R Programming Basics/5. Conditional Statements Training Exercise - Solutions Walkthrough.vtt 15.43 KB
    26. Machine Learning with R - Decision Trees and Random Forests/2. Decision Trees and Random Forests with R.vtt 15.28 KB
    22. Machine Learning with R - Logistic Regression/1. Introduction to Logistic Regression.vtt 15.2 KB
    13. Advanced R Programming/6. Dates and Timestamps.vtt 14.81 KB
    16. Data Visualization Project/2. Data Visualization Project - Solutions Walkthrough - Part 1.vtt 14.79 KB
    16. Data Visualization Project/3. Data Visualization Project Solutions Walkthrough - Part 2.vtt 14.62 KB
    11. Data Input and Output with R/4. SQL with R.vtt 14.41 KB
    20. Machine Learning with R - Linear Regression/4. Linear Regression with R - Part 3.vtt 13.98 KB
    29. Machine Learning Project - Support Vector Machines/2. Support Vector Machines Project - Solutions Part 1.vtt 13.77 KB
    21. Machine Learning Project - Linear Regression/3. ML - Linear Regression Project - Solutions Part 2.vtt 13.55 KB
    6. Development Environment Overview/2. Course Notes.vtt 13.17 KB
    8. R Matrices/2. Creating a Matrix.vtt 12.98 KB
    29. Machine Learning Project - Support Vector Machines/3. Support Vector Machines Project - Solutions Part 2.vtt 12.8 KB
    14. Data Manipulation with R/3. Guide to Using Dplyr - Part 2.vtt 12.67 KB
    30. Machine Learning with R - K-means Clustering/2. K Means Clustering with R.vtt 12.61 KB
    21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.vtt 12.57 KB
    15. Data Visualization with R/7. Coordinates and Faceting.vtt 12.54 KB
    7. Introduction to R Basics/8. Vector Indexing and Slicing.vtt 12.53 KB
    25. Machine Learning Project - K Nearest Neighbors/2. K Nearest Neighbors Project Solutions.vtt 12.06 KB
    17. Interactive Visualizations with Plotly/1. Overview of Plotly and Interactive Visualizations.vtt 11.79 KB
    18. Capstone Data Project/1. Introduction to Capstone Project.vtt 11.49 KB
    9. R Data Frames/3. Data Frame Indexing and Selection.vtt 11.47 KB
    10. R Lists/1. List Basics.vtt 11.47 KB
    13. Advanced R Programming/2. Built-in R Features.vtt 11.19 KB
    34. Machine Learning Project - Neural Nets/2. Neural Nets Project - Solutions.vtt 10.99 KB
    9. R Data Frames/2. Data Frame Basics.vtt 10.63 KB
    15. Data Visualization with R/4. Barplots.vtt 10.32 KB
    8. R Matrices/6. Factor and Categorical Matrices.vtt 10.18 KB
    12. R Programming Basics/2. Logical Operators.vtt 10.09 KB
    15. Data Visualization with R/5. Boxplots.vtt 9.63 KB
    11. Data Input and Output with R/5. Web Scraping with R.vtt 9.36 KB
    15. Data Visualization with R/6. 2 Variable Plotting.vtt 9.29 KB
    12. R Programming Basics/6. While Loops.vtt 9.23 KB
    15. Data Visualization with R/1. Overview of ggplot2.vtt 9.19 KB
    7. Introduction to R Basics/11. R Basics Training Exercise - Solutions Walkthrough.vtt 9.12 KB
    3. Windows Installation Set-Up/1. Windows Installation Procedure.vtt 9.05 KB
    7. Introduction to R Basics/5. Vector Basics.vtt 8.99 KB
    8. R Matrices/5. Matrix Selection and Indexing.vtt 8.6 KB
    7. Introduction to R Basics/7. Comparison Operators.vtt 8.5 KB
    14. Data Manipulation with R/4. Pipe Operator.vtt 8.39 KB
    33. Machine Learning with R - Neural Nets/1. Introduction to Neural Nets.vtt 8.38 KB
    26. Machine Learning with R - Decision Trees and Random Forests/1. Introduction to Tree Methods.vtt 8.34 KB
    11. Data Input and Output with R/2. CSV Files with R.vtt 8.29 KB
    4. Mac OS Installation Set-Up/1. Mac OS Installation Procedure.vtt 7.8 KB
    20. Machine Learning with R - Linear Regression/1. Introduction to Linear Regression.vtt 7.3 KB
    15. Data Visualization with R/8. Themes.vtt 6.88 KB
    32. Machine Learning with R - Natural Language Processing/2. Natural Language Processing with R - Part 1.vtt 6.86 KB
    8. R Matrices/4. Matrix Operations.vtt 6.81 KB
    7. Introduction to R Basics/4. R Basic Data Types.vtt 6.81 KB
    7. Introduction to R Basics/3. Variables.vtt 6.64 KB
    24. Machine Learning with R - K Nearest Neighbors/1. Introduction to K Nearest Neighbors.vtt 6.46 KB
    27. Machine Learning Project - Decision Trees and Random Forests/3. Tree Methods Project Solutions - Part 2.vtt 6.44 KB
    30. Machine Learning with R - K-means Clustering/1. Introduction to K-Means Clustering.vtt 6.33 KB
    13. Advanced R Programming/5. Regular Expressions.vtt 6.16 KB
    7. Introduction to R Basics/2. Arithmetic in R.vtt 5.83 KB
    8. R Matrices/3. Matrix Arithmetic.vtt 5.81 KB
    35. Bonus Section - Discounts for Other Courses/1. Bonus Lecture Coupons.html 5.79 KB
    7. Introduction to R Basics/6. Vector Operations.vtt 5.72 KB
    32. Machine Learning with R - Natural Language Processing/1. Introduction to Natural Language Processing.vtt 5.6 KB
    28. Machine Learning with R - Support Vector Machines/1. Introduction to Support Vector Machines.vtt 5.5 KB
    1. Course Introduction/3. What is Data Science.vtt 5.23 KB
    25. Machine Learning Project - K Nearest Neighbors/1. Introduction K Nearest Neighbors Project.vtt 4.78 KB
    13. Advanced R Programming/4. Math Functions with R.vtt 4.43 KB
    16. Data Visualization Project/1. Data Visualization Project.vtt 4.22 KB
    15. Data Visualization with R/9. ggplot2 Exercises.vtt 4.07 KB
    7. Introduction to R Basics/1. Introduction to R Basics.vtt 3.69 KB
    1. Course Introduction/1. Introduction to Course.vtt 3.57 KB
    29. Machine Learning Project - Support Vector Machines/1. Introduction to SVM Project.vtt 3.51 KB
    12. R Programming Basics/9. Functions Training Exercise.vtt 3.49 KB
    34. Machine Learning Project - Neural Nets/1. Introduction to Neural Nets Project.vtt 3.23 KB
    7. Introduction to R Basics/10. R Basics Training Exercise.vtt 3.14 KB
    31. Machine Learning Project - K-means Clustering/1. Introduction to K Means Clustering Project.vtt 3.13 KB
    1. Course Introduction/2. Course Curriculum.vtt 3.06 KB
    7. Introduction to R Basics/9. Getting Help with R and RStudio.vtt 2.99 KB
    23. Machine Learning Project - Logistic Regression/1. Introduction to Logistic Regression Project.vtt 2.55 KB
    27. Machine Learning Project - Decision Trees and Random Forests/1. Introduction to Decision Trees and Random Forests Project.vtt 2.53 KB
    12. R Programming Basics/4. Conditional Statements Training Exercise.vtt 2.28 KB
    2. Course Best Practices/1. How to Get Help in the Course!.html 2 KB
    14. Data Manipulation with R/6. Dplyr Training Exercise.vtt 1.79 KB
    9. R Data Frames/6. Data Frame Training Exercise.vtt 1.57 KB
    5. Linux Installation/1. LinuxUnbuntu Installation Procedure.html 1.49 KB
    12. R Programming Basics/1. Introduction to Programming Basics.vtt 1.42 KB
    8. R Matrices/7. Matrix Training Exercise.vtt 1.4 KB
    13. Advanced R Programming/1. Introduction to Advanced R Programming.vtt 1.39 KB
    1. Course Introduction/4. Course FAQ.html 1.3 KB
    8. R Matrices/1. Introduction to R Matrices.vtt 1.13 KB
    9. R Data Frames/1. Introduction to R Data Frames.vtt 1022 B
    17. Interactive Visualizations with Plotly/2. Resources for Plotly and ggplot2.html 962 B
    14. Data Manipulation with R/1. Data Manipulation Overview.vtt 945 B
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    11. Data Input and Output with R/1. Introduction to Data Input and Output with R.vtt 462 B
    6. Development Environment Overview/1. Development Environment Overview.vtt 451 B
    19. Introduction to Machine Learning with R/1. ISLR PDF.html 393 B
    2. Course Best Practices/3. Installation and Set-Up.html 335 B
    14. Data Manipulation with R/5. Quick note on Dpylr exercise.html 309 B
    2. Course Best Practices/2. Welcome to the Course..html 155 B
    8. R Matrices/4.1 Reference of Built-in Functions.html 117 B
    [DesireCourse.Com].url 51 B

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