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种子名称： [FreeCourseSite.com] Udemy - Data Science and Machine Learning Bootcamp with R
文件类型： 视频
文件数目： 119个文件
文件大小： 2.77 GB
收录时间： 2021-7-14 07:52
已经下载： 3次
资源热度： 139
最近下载： 2024-9-29 16:57

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[FreeCourseSite.com] Udemy - Data Science and Machine Learning Bootcamp with R.torrent

1. Course Introduction/1. Introduction to Course.mp417.36MB

1. Course Introduction/2. Course Curriculum.mp46.72MB

1. Course Introduction/3. What is Data Science.mp47.8MB

10. R Lists/1. List Basics.mp421.9MB

11. Data Input and Output with R/1. Introduction to Data Input and Output with R.mp41MB

11. Data Input and Output with R/2. CSV Files with R.mp414.06MB

11. Data Input and Output with R/4. Excel Files with R.mp427.7MB

11. Data Input and Output with R/5. SQL with R.mp433.44MB

11. Data Input and Output with R/6. Web Scraping with R.mp422.79MB

12. R Programming Basics/1. Introduction to Programming Basics.mp41.88MB

12. R Programming Basics/10. Functions Training Exercise - Solutions.mp443.39MB

12. R Programming Basics/2. Logical Operators.mp416.19MB

12. R Programming Basics/3. if, else, and else if Statements.mp429.16MB

12. R Programming Basics/4. Conditional Statements Training Exercise.mp44.35MB

12. R Programming Basics/5. Conditional Statements Training Exercise - Solutions Walkthrough.mp424.2MB

12. R Programming Basics/6. While Loops.mp413.55MB

12. R Programming Basics/7. For Loops.mp426.55MB

12. R Programming Basics/8. Functions.mp440.63MB

12. R Programming Basics/9. Functions Training Exercise.mp48.57MB

13. Advanced R Programming/1. Introduction to Advanced R Programming.mp41.79MB

13. Advanced R Programming/2. Built-in R Features.mp420.4MB

13. Advanced R Programming/3. Apply.mp431.4MB

13. Advanced R Programming/4. Math Functions with R.mp412.96MB

13. Advanced R Programming/5. Regular Expressions.mp411.03MB

13. Advanced R Programming/6. Dates and Timestamps.mp427.85MB

14. Data Manipulation with R/1. Data Manipulation Overview.mp41.25MB

14. Data Manipulation with R/2. Guide to Using Dplyr.mp429.44MB

14. Data Manipulation with R/3. Guide to Using Dplyr - Part 2.mp424.15MB

14. Data Manipulation with R/4. Pipe Operator.mp416.63MB

14. Data Manipulation with R/6. Dplyr Training Exercise.mp43.1MB

14. Data Manipulation with R/7. Dplyr Training Exercise - Solutions Walkthrough.mp415.64MB

14. Data Manipulation with R/8. Guide to Using Tidyr.mp457.73MB

15. Data Visualization with R/1. Overview of ggplot2.mp413.33MB

15. Data Visualization with R/10. ggplot2 Exercise Solutions.mp430.53MB

15. Data Visualization with R/2. Histograms.mp456.96MB

15. Data Visualization with R/3. Scatterplots.mp445.19MB

15. Data Visualization with R/4. Barplots.mp419.97MB

15. Data Visualization with R/5. Boxplots.mp416.69MB

15. Data Visualization with R/6. 2 Variable Plotting.mp424.74MB

15. Data Visualization with R/7. Coordinates and Faceting.mp428.05MB

15. Data Visualization with R/8. Themes.mp413.36MB

15. Data Visualization with R/9. ggplot2 Exercises.mp48.32MB

16. Data Visualization Project/1. Data Visualization Project.mp415.24MB

16. Data Visualization Project/2. Data Visualization Project - Solutions Walkthrough - Part 1.mp442.02MB

16. Data Visualization Project/3. Data Visualization Project Solutions Walkthrough - Part 2.mp441.47MB

17. Interactive Visualizations with Plotly/1. Overview of Plotly and Interactive Visualizations.mp442.52MB

18. Capstone Data Project/1. Introduction to Capstone Project.mp445.51MB

18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.mp463.29MB

19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.mp459.75MB

20. Machine Learning with R - Linear Regression/1. Introduction to Linear Regression.mp411.56MB

20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.mp455.61MB

20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.mp453.99MB

20. Machine Learning with R - Linear Regression/4. Linear Regression with R - Part 3.mp426.3MB

21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.mp446.51MB

21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.mp459.54MB

21. Machine Learning Project - Linear Regression/3. ML - Linear Regression Project - Solutions Part 2.mp432.73MB

22. Machine Learning with R - Logistic Regression/1. Introduction to Logistic Regression.mp421.91MB

22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.mp446.34MB

22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.mp447.57MB

23. Machine Learning Project - Logistic Regression/1. Introduction to Logistic Regression Project.mp413.38MB

23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.mp456.28MB

23. Machine Learning Project - Logistic Regression/3. Logistic Regression Project Solutions - Part 2.mp438.64MB

23. Machine Learning Project - Logistic Regression/4. Logistic Regression Project - Solutions Part 3.mp437.63MB

24. Machine Learning with R - K Nearest Neighbors/1. Introduction to K Nearest Neighbors.mp49.27MB

24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.mp446.74MB

25. Machine Learning Project - K Nearest Neighbors/1. Introduction K Nearest Neighbors Project.mp414.69MB

25. Machine Learning Project - K Nearest Neighbors/2. K Nearest Neighbors Project Solutions.mp430.42MB

26. Machine Learning with R - Decision Trees and Random Forests/1. Introduction to Tree Methods.mp412.48MB

26. Machine Learning with R - Decision Trees and Random Forests/2. Decision Trees and Random Forests with R.mp434.4MB

27. Machine Learning Project - Decision Trees and Random Forests/1. Introduction to Decision Trees and Random Forests Project.mp410.16MB

27. Machine Learning Project - Decision Trees and Random Forests/2. Tree Methods Project Solutions - Part 1.mp438.86MB

27. Machine Learning Project - Decision Trees and Random Forests/3. Tree Methods Project Solutions - Part 2.mp410.49MB

28. Machine Learning with R - Support Vector Machines/1. Introduction to Support Vector Machines.mp48.97MB

28. Machine Learning with R - Support Vector Machines/2. Support Vector Machines with R.mp439.57MB

29. Machine Learning Project - Support Vector Machines/1. Introduction to SVM Project.mp411.5MB

29. Machine Learning Project - Support Vector Machines/2. Support Vector Machines Project - Solutions Part 1.mp428.49MB

29. Machine Learning Project - Support Vector Machines/3. Support Vector Machines Project - Solutions Part 2.mp424.31MB

3. Windows Installation Set-Up/1. Windows Installation Procedure.mp424.52MB

30. Machine Learning with R - K-means Clustering/1. Introduction to K-Means Clustering.mp49.58MB

30. Machine Learning with R - K-means Clustering/2. K Means Clustering with R.mp422.53MB

31. Machine Learning Project - K-means Clustering/1. Introduction to K Means Clustering Project.mp48.81MB

31. Machine Learning Project - K-means Clustering/2. K Means Clustering Project - Solutions Walkthrough.mp438.21MB

32. Machine Learning with R - Natural Language Processing/1. Introduction to Natural Language Processing.mp48.3MB

32. Machine Learning with R - Natural Language Processing/2. Natural Language Processing with R - Part 1.mp412.62MB

32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.mp442.85MB

33. Machine Learning with R - Neural Nets/1. Introduction to Neural Nets.mp412.65MB

33. Machine Learning with R - Neural Nets/2. Neural Nets with R.mp454.77MB

34. Machine Learning Project - Neural Nets/1. Introduction to Neural Nets Project.mp411.09MB

34. Machine Learning Project - Neural Nets/2. Neural Nets Project - Solutions.mp425.52MB

4. Mac OS Installation Set-Up/1. Mac OS Installation Procedure.mp471.47MB

6. Development Environment Overview/1. Development Environment Overview.mp41.11MB

6. Development Environment Overview/2. Course Notes.mp431.06MB

6. Development Environment Overview/3. Guide to RStudio.mp435.06MB

7. Introduction to R Basics/1. Introduction to R Basics.mp46.44MB

7. Introduction to R Basics/10. R Basics Training Exercise.mp46.53MB

7. Introduction to R Basics/11. R Basics Training Exercise - Solutions Walkthrough.mp414.75MB

7. Introduction to R Basics/2. Arithmetic in R.mp48.49MB

7. Introduction to R Basics/3. Variables.mp49.9MB

7. Introduction to R Basics/4. R Basic Data Types.mp49.93MB

7. Introduction to R Basics/5. Vector Basics.mp415.26MB

7. Introduction to R Basics/6. Vector Operations.mp48.44MB

7. Introduction to R Basics/7. Comparison Operators.mp411.85MB

7. Introduction to R Basics/8. Vector Indexing and Slicing.mp417.9MB

7. Introduction to R Basics/9. Getting Help with R and RStudio.mp46.81MB

8. R Matrices/1. Introduction to R Matrices.mp41.61MB

8. R Matrices/2. Creating a Matrix.mp421.25MB

8. R Matrices/3. Matrix Arithmetic.mp48.85MB

8. R Matrices/4. Matrix Operations.mp412.84MB

8. R Matrices/5. Matrix Selection and Indexing.mp413.31MB

8. R Matrices/6. Factor and Categorical Matrices.mp417MB

8. R Matrices/7. Matrix Training Exercise.mp43.84MB

8. R Matrices/8. Matrix Training Exercises - Solutions Walkthrough.mp428.1MB

9. R Data Frames/1. Introduction to R Data Frames.mp41.49MB

9. R Data Frames/2. Data Frame Basics.mp421.46MB

9. R Data Frames/3. Data Frame Indexing and Selection.mp419.02MB

9. R Data Frames/4. Overview of Data Frame Operations - Part 1.mp434.59MB

9. R Data Frames/5. Overview of Data Frame Operations - Part 2.mp438.92MB

9. R Data Frames/6. Data Frame Training Exercise.mp44.99MB

9. R Data Frames/7. Data Frame Training Exercises - Solutions Walkthrough.mp434.06MB