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

Creation Time	July 6, 2024, 8:36 p.m.
Last Access Time	Oct. 17, 2024, 1:21 p.m.
File Size	2.4 GB
Keywords	and Data with Science - Udemy Machine R Learning DesireCourse Bootcamp Com
Total Requests	20
Total Files	253
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18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.mp4 54.5 MB
19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.mp4 48.5 MB
21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.mp4 47.8 MB
23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.mp4 47.4 MB
14. Data Manipulation with R/8. Guide to Using Tidyr.mp4 47.1 MB
20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.mp4 46.9 MB
33. Machine Learning with R - Neural Nets/2. Neural Nets with R.mp4 46.3 MB
20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.mp4 45.9 MB
15. Data Visualization with R/2. Histograms.mp4 45.6 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 40.9 MB
24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.mp4 40.4 MB
22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.mp4 39.6 MB
15. Data Visualization with R/3. Scatterplots.mp4 37.5 MB
12. R Programming Basics/10. Functions Training Exercise - Solutions.mp4 36.8 MB
32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.mp4 35.7 MB
12. R Programming Basics/8. Functions.mp4 35.1 MB
18. Capstone Data Project/1. Introduction to Capstone Project.mp4 35.0 MB
9. R Data Frames/5. Overview of Data Frame Operations - Part 2.mp4 34.1 MB
21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.mp4 33.7 MB
17. Interactive Visualizations with Plotly/1. Overview of Plotly and Interactive Visualizations.mp4 33.5 MB
27. Machine Learning Project - Decision Trees and Random Forests/2. Tree Methods Project Solutions - Part 1.mp4 33.4 MB
28. Machine Learning with R - Support Vector Machines/2. Support Vector Machines with R.mp4 33.0 MB
31. Machine Learning Project - K-means Clustering/2. K Means Clustering Project - Solutions Walkthrough.mp4 33.0 MB
23. Machine Learning Project - Logistic Regression/3. Logistic Regression Project Solutions - Part 2.mp4 32.8 MB
16. Data Visualization Project/2. Data Visualization Project - Solutions Walkthrough - Part 1.mp4 32.6 MB
23. Machine Learning Project - Logistic Regression/4. Logistic Regression Project - Solutions Part 3.mp4 32.2 MB
16. Data Visualization Project/3. Data Visualization Project Solutions Walkthrough - Part 2.mp4 32.1 MB
9. R Data Frames/4. Overview of Data Frame Operations - Part 1.mp4 30.5 MB
9. R Data Frames/7. Data Frame Training Exercises - Solutions Walkthrough.mp4 29.0 MB
26. Machine Learning with R - Decision Trees and Random Forests/2. Decision Trees and Random Forests with R.mp4 28.8 MB
6. Development Environment Overview/3. Guide to RStudio.mp4 28.3 MB
13. Advanced R Programming/3. Apply.mp4 28.1 MB
21. Machine Learning Project - Linear Regression/3. ML - Linear Regression Project - Solutions Part 2.mp4 26.1 MB
15. Data Visualization with R/10. ggplot2 Exercise Solutions.mp4 26.0 MB
12. R Programming Basics/3. if, else, and else if Statements.mp4 25.9 MB
6. Development Environment Overview/2. Course Notes.mp4 25.7 MB
11. Data Input and Output with R/4. SQL with R.mp4 25.5 MB
25. Machine Learning Project - K Nearest Neighbors/2. K Nearest Neighbors Project Solutions.mp4 25.2 MB
14. Data Manipulation with R/2. Guide to Using Dplyr.mp4 25.1 MB
8. R Matrices/8. Matrix Training Exercises - Solutions Walkthrough.mp4 24.6 MB
11. Data Input and Output with R/3. Excel Files with R.mp4 24.2 MB
29. Machine Learning Project - Support Vector Machines/2. Support Vector Machines Project - Solutions Part 1.mp4 24.1 MB
15. Data Visualization with R/7. Coordinates and Faceting.mp4 24.1 MB
13. Advanced R Programming/6. Dates and Timestamps.mp4 24.0 MB
12. R Programming Basics/7. For Loops.mp4 23.1 MB
20. Machine Learning with R - Linear Regression/4. Linear Regression with R - Part 3.mp4 22.8 MB
12. R Programming Basics/5. Conditional Statements Training Exercise - Solutions Walkthrough.mp4 21.1 MB
29. Machine Learning Project - Support Vector Machines/3. Support Vector Machines Project - Solutions Part 2.mp4 21.0 MB
4. Mac OS Installation Set-Up/1. Mac OS Installation Procedure.mp4 20.8 MB
34. Machine Learning Project - Neural Nets/2. Neural Nets Project - Solutions.mp4 20.6 MB
14. Data Manipulation with R/3. Guide to Using Dplyr - Part 2.mp4 20.5 MB
15. Data Visualization with R/6. 2 Variable Plotting.mp4 20.4 MB
22. Machine Learning with R - Logistic Regression/1. Introduction to Logistic Regression.mp4 19.8 MB
10. R Lists/1. List Basics.mp4 19.6 MB
30. Machine Learning with R - K-means Clustering/2. K Means Clustering with R.mp4 19.2 MB
8. R Matrices/2. Creating a Matrix.mp4 18.6 MB
9. R Data Frames/2. Data Frame Basics.mp4 18.2 MB
13. Advanced R Programming/2. Built-in R Features.mp4 18.0 MB
3. Windows Installation Set-Up/1. Windows Installation Procedure.mp4 17.8 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 16.8 MB
15. Data Visualization with R/4. Barplots.mp4 16.8 MB
7. Introduction to R Basics/8. Vector Indexing and Slicing.mp4 16.1 MB
8. R Matrices/6. Factor and Categorical Matrices.mp4 14.8 MB
12. R Programming Basics/2. Logical Operators.mp4 14.5 MB
15. Data Visualization with R/5. Boxplots.mp4 14.1 MB
14. Data Manipulation with R/7. Dplyr Training Exercise - Solutions Walkthrough.vtt 13.8 MB
14. Data Manipulation with R/7. Dplyr Training Exercise - Solutions Walkthrough.mp4 13.8 MB
14. Data Manipulation with R/4. Pipe Operator.mp4 13.8 MB
7. Introduction to R Basics/5. Vector Basics.mp4 13.7 MB
7. Introduction to R Basics/11. R Basics Training Exercise - Solutions Walkthrough.mp4 12.8 MB
1. Course Introduction/1. Introduction to Course.mp4 12.4 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 12.0 MB
15. Data Visualization with R/1. Overview of ggplot2.mp4 12.0 MB
8. R Matrices/5. Matrix Selection and Indexing.mp4 11.8 MB
25. Machine Learning Project - K Nearest Neighbors/1. Introduction K Nearest Neighbors Project.mp4 11.7 MB
16. Data Visualization Project/1. Data Visualization Project.mp4 11.6 MB
26. Machine Learning with R - Decision Trees and Random Forests/1. Introduction to Tree Methods.mp4 11.2 MB
15. Data Visualization with R/8. Themes.mp4 11.2 MB
33. Machine Learning with R - Neural Nets/1. Introduction to Neural Nets.mp4 11.2 MB
8. R Matrices/4. Matrix Operations.mp4 10.8 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 10.4 MB
20. Machine Learning with R - Linear Regression/1. Introduction to Linear Regression.mp4 10.2 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 9.7 MB
29. Machine Learning Project - Support Vector Machines/1. Introduction to SVM Project.mp4 9.3 MB
13. Advanced R Programming/4. Math Functions with R.mp4 9.2 MB
27. Machine Learning Project - Decision Trees and Random Forests/3. Tree Methods Project Solutions - Part 2.mp4 9.1 MB
7. Introduction to R Basics/4. R Basic Data Types.mp4 9.1 MB
7. Introduction to R Basics/3. Variables.mp4 8.9 MB
30. Machine Learning with R - K-means Clustering/1. Introduction to K-Means Clustering.mp4 8.6 MB
24. Machine Learning with R - K Nearest Neighbors/1. Introduction to K Nearest Neighbors.mp4 8.5 MB
27. Machine Learning Project - Decision Trees and Random Forests/1. Introduction to Decision Trees and Random Forests Project.mp4 8.4 MB
34. Machine Learning Project - Neural Nets/1. Introduction to Neural Nets Project.mp4 8.4 MB
28. Machine Learning with R - Support Vector Machines/1. Introduction to Support Vector Machines.mp4 8.0 MB
8. R Matrices/3. Matrix Arithmetic.mp4 7.8 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 7.6 MB
7. Introduction to R Basics/6. Vector Operations.mp4 7.5 MB
31. Machine Learning Project - K-means Clustering/1. Introduction to K Means Clustering Project.mp4 7.2 MB
1. Course Introduction/3. What is Data Science.mp4 7.0 MB
15. Data Visualization with R/9. ggplot2 Exercises.mp4 6.7 MB
12. R Programming Basics/9. Functions Training Exercise.mp4 6.7 MB
1. Course Introduction/2. Course Curriculum.mp4 5.7 MB
7. Introduction to R Basics/9. Getting Help with R and RStudio.mp4 5.6 MB
7. Introduction to R Basics/1. Introduction to R Basics.mp4 5.6 MB
7. Introduction to R Basics/10. R Basics Training Exercise.mp4 5.4 MB
9. R Data Frames/6. Data Frame Training Exercise.mp4 4.3 MB
12. R Programming Basics/4. Conditional Statements Training Exercise.mp4 3.5 MB
8. R Matrices/7. Matrix Training Exercise.mp4 3.2 MB
19. Introduction to Machine Learning with R/2.1 Machine Learning Slides.zip.zip 2.9 MB
14. Data Manipulation with R/6. Dplyr Training Exercise.mp4 2.7 MB
12. R Programming Basics/1. Introduction to Programming Basics.mp4 1.7 MB
13. Advanced R Programming/1. Introduction to Advanced R Programming.mp4 1.6 MB
8. R Matrices/1. Introduction to R Matrices.mp4 1.5 MB
9. R Data Frames/1. Introduction to R Data Frames.mp4 1.4 MB
14. Data Manipulation with R/1. Data Manipulation Overview.mp4 1.2 MB
6. Development Environment Overview/1. Development Environment Overview.mp4 870.3 KB
11. Data Input and Output with R/1. Introduction to Data Input and Output with R.mp4 869.7 KB
33. Machine Learning with R - Neural Nets/2. Neural Nets with R.vtt 28.1 KB
20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.vtt 26.8 KB
18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.vtt 26.2 KB
21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.vtt 26.0 KB
12. R Programming Basics/10. Functions Training Exercise - Solutions.vtt 25.4 KB
20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.vtt 25.1 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 24.9 KB
15. Data Visualization with R/2. Histograms.vtt 24.8 KB
23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.vtt 24.7 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 23.8 KB
12. R Programming Basics/8. Functions.vtt 23.3 KB
24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.vtt 22.5 KB
22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.vtt 22.2 KB
9. R Data Frames/4. Overview of Data Frame Operations - Part 1.vtt 21.8 KB
15. Data Visualization with R/3. Scatterplots.vtt 21.3 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 20.3 KB
23. Machine Learning Project - Logistic Regression/3. Logistic Regression Project Solutions - Part 2.vtt 19.4 KB
28. Machine Learning with R - Support Vector Machines/2. Support Vector Machines with R.vtt 18.6 KB
9. R Data Frames/7. Data Frame Training Exercises - Solutions Walkthrough.vtt 18.5 KB
32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.vtt 18.1 KB
13. Advanced R Programming/3. Apply.vtt 17.9 KB
12. R Programming Basics/3. if, else, and else if Statements.vtt 17.7 KB
23. Machine Learning Project - Logistic Regression/4. Logistic Regression Project - Solutions Part 3.vtt 17.2 KB
15. Data Visualization with R/10. ggplot2 Exercise Solutions.vtt 17.1 KB
6. Development Environment Overview/3. Guide to RStudio.vtt 17.0 KB
8. R Matrices/8. Matrix Training Exercises - Solutions Walkthrough.vtt 17.0 KB
12. R Programming Basics/7. For Loops.vtt 16.0 KB
14. Data Manipulation with R/2. Guide to Using Dplyr.vtt 15.9 KB
11. Data Input and Output with R/3. Excel Files with R.vtt 15.7 KB
12. R Programming Basics/5. Conditional Statements Training Exercise - Solutions Walkthrough.vtt 15.4 KB
26. Machine Learning with R - Decision Trees and Random Forests/2. Decision Trees and Random Forests with R.vtt 15.3 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 14.8 KB
16. Data Visualization Project/2. Data Visualization Project - Solutions Walkthrough - Part 1.vtt 14.8 KB
16. Data Visualization Project/3. Data Visualization Project Solutions Walkthrough - Part 2.vtt 14.6 KB
11. Data Input and Output with R/4. SQL with R.vtt 14.4 KB
20. Machine Learning with R - Linear Regression/4. Linear Regression with R - Part 3.vtt 14.0 KB
29. Machine Learning Project - Support Vector Machines/2. Support Vector Machines Project - Solutions Part 1.vtt 13.8 KB
21. Machine Learning Project - Linear Regression/3. ML - Linear Regression Project - Solutions Part 2.vtt 13.5 KB
6. Development Environment Overview/2. Course Notes.vtt 13.2 KB
8. R Matrices/2. Creating a Matrix.vtt 13.0 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 12.7 KB
30. Machine Learning with R - K-means Clustering/2. K Means Clustering with R.vtt 12.6 KB
21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.vtt 12.6 KB
15. Data Visualization with R/7. Coordinates and Faceting.vtt 12.5 KB
7. Introduction to R Basics/8. Vector Indexing and Slicing.vtt 12.5 KB
25. Machine Learning Project - K Nearest Neighbors/2. K Nearest Neighbors Project Solutions.vtt 12.1 KB
17. Interactive Visualizations with Plotly/1. Overview of Plotly and Interactive Visualizations.vtt 11.8 KB
18. Capstone Data Project/1. Introduction to Capstone Project.vtt 11.5 KB
9. R Data Frames/3. Data Frame Indexing and Selection.vtt 11.5 KB
10. R Lists/1. List Basics.vtt 11.5 KB
13. Advanced R Programming/2. Built-in R Features.vtt 11.2 KB
34. Machine Learning Project - Neural Nets/2. Neural Nets Project - Solutions.vtt 11.0 KB
9. R Data Frames/2. Data Frame Basics.vtt 10.6 KB
15. Data Visualization with R/4. Barplots.vtt 10.3 KB
8. R Matrices/6. Factor and Categorical Matrices.vtt 10.2 KB
12. R Programming Basics/2. Logical Operators.vtt 10.1 KB
15. Data Visualization with R/5. Boxplots.vtt 9.6 KB
11. Data Input and Output with R/5. Web Scraping with R.vtt 9.4 KB
15. Data Visualization with R/6. 2 Variable Plotting.vtt 9.3 KB
12. R Programming Basics/6. While Loops.vtt 9.2 KB
15. Data Visualization with R/1. Overview of ggplot2.vtt 9.2 KB
7. Introduction to R Basics/11. R Basics Training Exercise - Solutions Walkthrough.vtt 9.1 KB
3. Windows Installation Set-Up/1. Windows Installation Procedure.vtt 9.1 KB
7. Introduction to R Basics/5. Vector Basics.vtt 9.0 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 8.4 KB
33. Machine Learning with R - Neural Nets/1. Introduction to Neural Nets.vtt 8.4 KB
26. Machine Learning with R - Decision Trees and Random Forests/1. Introduction to Tree Methods.vtt 8.3 KB
11. Data Input and Output with R/2. CSV Files with R.vtt 8.3 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 6.9 KB
32. Machine Learning with R - Natural Language Processing/2. Natural Language Processing with R - Part 1.vtt 6.9 KB
8. R Matrices/4. Matrix Operations.vtt 6.8 KB
7. Introduction to R Basics/4. R Basic Data Types.vtt 6.8 KB
7. Introduction to R Basics/3. Variables.vtt 6.6 KB
24. Machine Learning with R - K Nearest Neighbors/1. Introduction to K Nearest Neighbors.vtt 6.5 KB
27. Machine Learning Project - Decision Trees and Random Forests/3. Tree Methods Project Solutions - Part 2.vtt 6.4 KB
30. Machine Learning with R - K-means Clustering/1. Introduction to K-Means Clustering.vtt 6.3 KB
13. Advanced R Programming/5. Regular Expressions.vtt 6.2 KB
7. Introduction to R Basics/2. Arithmetic in R.vtt 5.8 KB
8. R Matrices/3. Matrix Arithmetic.vtt 5.8 KB
35. Bonus Section - Discounts for Other Courses/1. Bonus Lecture Coupons.html 5.8 KB
7. Introduction to R Basics/6. Vector Operations.vtt 5.7 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 5.2 KB
25. Machine Learning Project - K Nearest Neighbors/1. Introduction K Nearest Neighbors Project.vtt 4.8 KB
13. Advanced R Programming/4. Math Functions with R.vtt 4.4 KB
16. Data Visualization Project/1. Data Visualization Project.vtt 4.2 KB
15. Data Visualization with R/9. ggplot2 Exercises.vtt 4.1 KB
7. Introduction to R Basics/1. Introduction to R Basics.vtt 3.7 KB
1. Course Introduction/1. Introduction to Course.vtt 3.6 KB
29. Machine Learning Project - Support Vector Machines/1. Introduction to SVM Project.vtt 3.5 KB
12. R Programming Basics/9. Functions Training Exercise.vtt 3.5 KB
34. Machine Learning Project - Neural Nets/1. Introduction to Neural Nets Project.vtt 3.2 KB
7. Introduction to R Basics/10. R Basics Training Exercise.vtt 3.1 KB
31. Machine Learning Project - K-means Clustering/1. Introduction to K Means Clustering Project.vtt 3.1 KB
1. Course Introduction/2. Course Curriculum.vtt 3.1 KB
7. Introduction to R Basics/9. Getting Help with R and RStudio.vtt 3.0 KB
23. Machine Learning Project - Logistic Regression/1. Introduction to Logistic Regression Project.vtt 2.6 KB
27. Machine Learning Project - Decision Trees and Random Forests/1. Introduction to Decision Trees and Random Forests Project.vtt 2.5 KB
12. R Programming Basics/4. Conditional Statements Training Exercise.vtt 2.3 KB
2. Course Best Practices/1. How to Get Help in the Course!.html 2.0 KB
14. Data Manipulation with R/6. Dplyr Training Exercise.vtt 1.8 KB
9. R Data Frames/6. Data Frame Training Exercise.vtt 1.6 KB
5. Linux Installation/1. LinuxUnbuntu Installation Procedure.html 1.5 KB
12. R Programming Basics/1. Introduction to Programming Basics.vtt 1.4 KB
8. R Matrices/7. Matrix Training Exercise.vtt 1.4 KB
13. Advanced R Programming/1. Introduction to Advanced R Programming.vtt 1.4 KB
1. Course Introduction/4. Course FAQ.html 1.3 KB
8. R Matrices/1. Introduction to R Matrices.vtt 1.1 KB
9. R Data Frames/1. Introduction to R Data Frames.vtt 1022 bytes
17. Interactive Visualizations with Plotly/2. Resources for Plotly and ggplot2.html 962 bytes
14. Data Manipulation with R/1. Data Manipulation Overview.vtt 945 bytes
[DesireCourse.Com].txt 754 bytes
11. Data Input and Output with R/1. Introduction to Data Input and Output with R.vtt 462 bytes
6. Development Environment Overview/1. Development Environment Overview.vtt 451 bytes
19. Introduction to Machine Learning with R/1. ISLR PDF.html 393 bytes
2. Course Best Practices/3. Installation and Set-Up.html 335 bytes
14. Data Manipulation with R/5. Quick note on Dpylr exercise.html 309 bytes
2. Course Best Practices/2. Welcome to the Course..html 155 bytes
8. R Matrices/4.1 Reference of Built-in Functions.html 117 bytes
[DesireCourse.Com].url 51 bytes

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