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[UdemyCourseDownloader] Data Science and Machine Learning Bootcamp with R

  • 收录时间:2021-01-01 15:03:00
  • 文件大小:2GB
  • 下载次数:2
  • 最近下载:2021-01-06 14:35:21
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文件列表

  1. 18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.mp4 54MB
  2. 19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.mp4 49MB
  3. 21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.mp4 48MB
  4. 23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.mp4 47MB
  5. 14. Data Manipulation with R/8. Guide to Using Tidyr.mp4 47MB
  6. 20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.mp4 47MB
  7. 33. Machine Learning with R - Neural Nets/2. Neural Nets with R.mp4 46MB
  8. 20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.mp4 46MB
  9. 15. Data Visualization with R/2. Histograms.mp4 46MB
  10. 01. Course Introduction/4.1 R-Course-HTML-Notes.zip.zip 46MB
  11. 06. Development Environment Overview/2.1 R-Course-HTML-Notes.zip.zip 46MB
  12. 22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.mp4 41MB
  13. 24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.mp4 40MB
  14. 22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.mp4 40MB
  15. 15. Data Visualization with R/3. Scatterplots.mp4 38MB
  16. 12. R Programming Basics/10. Functions Training Exercise - Solutions.mp4 37MB
  17. 32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.mp4 36MB
  18. 12. R Programming Basics/8. Functions.mp4 35MB
  19. 18. Capstone Data Project/1. Introduction to Capstone Project.mp4 35MB
  20. 09. R Data Frames/5. Overview of Data Frame Operations - Part 2.mp4 34MB
  21. 21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.mp4 34MB
  22. 17. Interactive Visualizations with Plotly/1. Overview of Plotly and Interactive Visualizations.mp4 34MB
  23. 27. Machine Learning Project - Decision Trees and Random Forests/2. Tree Methods Project Solutions - Part 1.mp4 33MB
  24. 28. Machine Learning with R - Support Vector Machines/2. Support Vector Machines with R.mp4 33MB
  25. 31. Machine Learning Project - K-means Clustering/2. K Means Clustering Project - Solutions Walkthrough.mp4 33MB
  26. 23. Machine Learning Project - Logistic Regression/3. Logistic Regression Project Solutions - Part 2.mp4 33MB
  27. 16. Data Visualization Project/2. Data Visualization Project - Solutions Walkthrough - Part 1.mp4 33MB
  28. 23. Machine Learning Project - Logistic Regression/4. Logistic Regression Project - Solutions Part 3.mp4 32MB
  29. 16. Data Visualization Project/3. Data Visualization Project Solutions Walkthrough - Part 2.mp4 32MB
  30. 09. R Data Frames/4. Overview of Data Frame Operations - Part 1.mp4 30MB
  31. 09. R Data Frames/7. Data Frame Training Exercises - Solutions Walkthrough.mp4 29MB
  32. 26. Machine Learning with R - Decision Trees and Random Forests/2. Decision Trees and Random Forests with R.mp4 29MB
  33. 06. Development Environment Overview/3. Guide to RStudio.mp4 28MB
  34. 13. Advanced R Programming/3. Apply.mp4 28MB
  35. 21. Machine Learning Project - Linear Regression/3. ML - Linear Regression Project - Solutions Part 2.mp4 26MB
  36. 15. Data Visualization with R/10. ggplot2 Exercise Solutions.mp4 26MB
  37. 12. R Programming Basics/3. if, else, and else if Statements.mp4 26MB
  38. 06. Development Environment Overview/2. Course Notes.mp4 26MB
  39. 11. Data Input and Output with R/4. SQL with R.mp4 25MB
  40. 25. Machine Learning Project - K Nearest Neighbors/2. K Nearest Neighbors Project Solutions.mp4 25MB
  41. 14. Data Manipulation with R/2. Guide to Using Dplyr.mp4 25MB
  42. 08. R Matrices/8. Matrix Training Exercises - Solutions Walkthrough.mp4 25MB
  43. 11. Data Input and Output with R/3. Excel Files with R.mp4 24MB
  44. 29. Machine Learning Project - Support Vector Machines/2. Support Vector Machines Project - Solutions Part 1.mp4 24MB
  45. 15. Data Visualization with R/7. Coordinates and Faceting.mp4 24MB
  46. 13. Advanced R Programming/6. Dates and Timestamps.mp4 24MB
  47. 12. R Programming Basics/7. For Loops.mp4 23MB
  48. 20. Machine Learning with R - Linear Regression/4. Linear Regression with R - Part 3.mp4 23MB
  49. 12. R Programming Basics/5. Conditional Statements Training Exercise - Solutions Walkthrough.mp4 21MB
  50. 29. Machine Learning Project - Support Vector Machines/3. Support Vector Machines Project - Solutions Part 2.mp4 21MB
  51. 04. Mac OS Installation Set-Up/1. Mac OS Installation Procedure.mp4 21MB
  52. 34. Machine Learning Project - Neural Nets/2. Neural Nets Project - Solutions.mp4 21MB
  53. 14. Data Manipulation with R/3. Guide to Using Dplyr - Part 2.mp4 21MB
  54. 15. Data Visualization with R/6. 2 Variable Plotting.mp4 20MB
  55. 22. Machine Learning with R - Logistic Regression/1. Introduction to Logistic Regression.mp4 20MB
  56. 10. R Lists/1. List Basics.mp4 20MB
  57. 30. Machine Learning with R - K-means Clustering/2. K Means Clustering with R.mp4 19MB
  58. 08. R Matrices/2. Creating a Matrix.mp4 19MB
  59. 09. R Data Frames/2. Data Frame Basics.mp4 18MB
  60. 13. Advanced R Programming/2. Built-in R Features.mp4 18MB
  61. 03. Windows Installation Set-Up/1. Windows Installation Procedure.mp4 18MB
  62. 11. Data Input and Output with R/5. Web Scraping with R.mp4 17MB
  63. 09. R Data Frames/3. Data Frame Indexing and Selection.mp4 17MB
  64. 15. Data Visualization with R/4. Barplots.mp4 17MB
  65. 07. Introduction to R Basics/8. Vector Indexing and Slicing.mp4 16MB
  66. 08. R Matrices/6. Factor and Categorical Matrices.mp4 15MB
  67. 12. R Programming Basics/2. Logical Operators.mp4 15MB
  68. 15. Data Visualization with R/5. Boxplots.mp4 14MB
  69. 14. Data Manipulation with R/7. Dplyr Training Exercise - Solutions Walkthrough.vtt 14MB
  70. 14. Data Manipulation with R/7. Dplyr Training Exercise - Solutions Walkthrough.mp4 14MB
  71. 14. Data Manipulation with R/4. Pipe Operator.mp4 14MB
  72. 07. Introduction to R Basics/5. Vector Basics.mp4 14MB
  73. 07. Introduction to R Basics/11. R Basics Training Exercise - Solutions Walkthrough.mp4 13MB
  74. 01. Course Introduction/1. Introduction to Course.mp4 12MB
  75. 11. Data Input and Output with R/2. CSV Files with R.mp4 12MB
  76. 12. R Programming Basics/6. While Loops.mp4 12MB
  77. 15. Data Visualization with R/1. Overview of ggplot2.mp4 12MB
  78. 08. R Matrices/5. Matrix Selection and Indexing.mp4 12MB
  79. 25. Machine Learning Project - K Nearest Neighbors/1. Introduction K Nearest Neighbors Project.mp4 12MB
  80. 16. Data Visualization Project/1. Data Visualization Project.mp4 12MB
  81. 26. Machine Learning with R - Decision Trees and Random Forests/1. Introduction to Tree Methods.mp4 11MB
  82. 15. Data Visualization with R/8. Themes.mp4 11MB
  83. 33. Machine Learning with R - Neural Nets/1. Introduction to Neural Nets.mp4 11MB
  84. 08. R Matrices/4. Matrix Operations.mp4 11MB
  85. 07. Introduction to R Basics/7. Comparison Operators.mp4 11MB
  86. 32. Machine Learning with R - Natural Language Processing/2. Natural Language Processing with R - Part 1.mp4 10MB
  87. 20. Machine Learning with R - Linear Regression/1. Introduction to Linear Regression.mp4 10MB
  88. 23. Machine Learning Project - Logistic Regression/1. Introduction to Logistic Regression Project.mp4 10MB
  89. 13. Advanced R Programming/5. Regular Expressions.mp4 10MB
  90. 29. Machine Learning Project - Support Vector Machines/1. Introduction to SVM Project.mp4 9MB
  91. 13. Advanced R Programming/4. Math Functions with R.mp4 9MB
  92. 27. Machine Learning Project - Decision Trees and Random Forests/3. Tree Methods Project Solutions - Part 2.mp4 9MB
  93. 07. Introduction to R Basics/4. R Basic Data Types.mp4 9MB
  94. 07. Introduction to R Basics/3. Variables.mp4 9MB
  95. 30. Machine Learning with R - K-means Clustering/1. Introduction to K-Means Clustering.mp4 9MB
  96. 24. Machine Learning with R - K Nearest Neighbors/1. Introduction to K Nearest Neighbors.mp4 9MB
  97. 27. Machine Learning Project - Decision Trees and Random Forests/1. Introduction to Decision Trees and Random Forests Project.mp4 8MB
  98. 34. Machine Learning Project - Neural Nets/1. Introduction to Neural Nets Project.mp4 8MB
  99. 28. Machine Learning with R - Support Vector Machines/1. Introduction to Support Vector Machines.mp4 8MB
  100. 08. R Matrices/3. Matrix Arithmetic.mp4 8MB
  101. 07. Introduction to R Basics/2. Arithmetic in R.mp4 8MB
  102. 32. Machine Learning with R - Natural Language Processing/1. Introduction to Natural Language Processing.mp4 8MB
  103. 07. Introduction to R Basics/6. Vector Operations.mp4 8MB
  104. 31. Machine Learning Project - K-means Clustering/1. Introduction to K Means Clustering Project.mp4 7MB
  105. 01. Course Introduction/3. What is Data Science.mp4 7MB
  106. 15. Data Visualization with R/9. ggplot2 Exercises.mp4 7MB
  107. 12. R Programming Basics/9. Functions Training Exercise.mp4 7MB
  108. 01. Course Introduction/2. Course Curriculum.mp4 6MB
  109. 07. Introduction to R Basics/9. Getting Help with R and RStudio.mp4 6MB
  110. 07. Introduction to R Basics/1. Introduction to R Basics.mp4 6MB
  111. 07. Introduction to R Basics/10. R Basics Training Exercise.mp4 5MB
  112. 09. R Data Frames/6. Data Frame Training Exercise.mp4 4MB
  113. 12. R Programming Basics/4. Conditional Statements Training Exercise.mp4 3MB
  114. 08. R Matrices/7. Matrix Training Exercise.mp4 3MB
  115. 19. Introduction to Machine Learning with R/2.1 Machine Learning Slides.zip.zip 3MB
  116. 14. Data Manipulation with R/6. Dplyr Training Exercise.mp4 3MB
  117. 12. R Programming Basics/1. Introduction to Programming Basics.mp4 2MB
  118. 13. Advanced R Programming/1. Introduction to Advanced R Programming.mp4 2MB
  119. 08. R Matrices/1. Introduction to R Matrices.mp4 1MB
  120. 09. R Data Frames/1. Introduction to R Data Frames.mp4 1MB
  121. 14. Data Manipulation with R/1. Data Manipulation Overview.mp4 1MB
  122. 06. Development Environment Overview/1. Development Environment Overview.mp4 870KB
  123. 11. Data Input and Output with R/1. Introduction to Data Input and Output with R.mp4 870KB
  124. 33. Machine Learning with R - Neural Nets/2. Neural Nets with R.vtt 28KB
  125. 20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.vtt 27KB
  126. 18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.vtt 26KB
  127. 21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.vtt 26KB
  128. 12. R Programming Basics/10. Functions Training Exercise - Solutions.vtt 25KB
  129. 20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.vtt 25KB
  130. 22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.vtt 25KB
  131. 14. Data Manipulation with R/8. Guide to Using Tidyr.vtt 25KB
  132. 15. Data Visualization with R/2. Histograms.vtt 25KB
  133. 23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.vtt 25KB
  134. 19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.vtt 24KB
  135. 09. R Data Frames/5. Overview of Data Frame Operations - Part 2.vtt 24KB
  136. 12. R Programming Basics/8. Functions.vtt 23KB
  137. 24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.vtt 23KB
  138. 22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.vtt 22KB
  139. 09. R Data Frames/4. Overview of Data Frame Operations - Part 1.vtt 22KB
  140. 15. Data Visualization with R/3. Scatterplots.vtt 21KB
  141. 31. Machine Learning Project - K-means Clustering/2. K Means Clustering Project - Solutions Walkthrough.vtt 21KB
  142. 27. Machine Learning Project - Decision Trees and Random Forests/2. Tree Methods Project Solutions - Part 1.vtt 20KB
  143. 23. Machine Learning Project - Logistic Regression/3. Logistic Regression Project Solutions - Part 2.vtt 19KB
  144. 28. Machine Learning with R - Support Vector Machines/2. Support Vector Machines with R.vtt 19KB
  145. 09. R Data Frames/7. Data Frame Training Exercises - Solutions Walkthrough.vtt 18KB
  146. 32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.vtt 18KB
  147. 13. Advanced R Programming/3. Apply.vtt 18KB
  148. 12. R Programming Basics/3. if, else, and else if Statements.vtt 18KB
  149. 23. Machine Learning Project - Logistic Regression/4. Logistic Regression Project - Solutions Part 3.vtt 17KB
  150. 15. Data Visualization with R/10. ggplot2 Exercise Solutions.vtt 17KB
  151. 06. Development Environment Overview/3. Guide to RStudio.vtt 17KB
  152. 08. R Matrices/8. Matrix Training Exercises - Solutions Walkthrough.vtt 17KB
  153. 12. R Programming Basics/7. For Loops.vtt 16KB
  154. 14. Data Manipulation with R/2. Guide to Using Dplyr.vtt 16KB
  155. 11. Data Input and Output with R/3. Excel Files with R.vtt 16KB
  156. 12. R Programming Basics/5. Conditional Statements Training Exercise - Solutions Walkthrough.vtt 15KB
  157. 26. Machine Learning with R - Decision Trees and Random Forests/2. Decision Trees and Random Forests with R.vtt 15KB
  158. 22. Machine Learning with R - Logistic Regression/1. Introduction to Logistic Regression.vtt 15KB
  159. 13. Advanced R Programming/6. Dates and Timestamps.vtt 15KB
  160. 16. Data Visualization Project/2. Data Visualization Project - Solutions Walkthrough - Part 1.vtt 15KB
  161. 16. Data Visualization Project/3. Data Visualization Project Solutions Walkthrough - Part 2.vtt 15KB
  162. 11. Data Input and Output with R/4. SQL with R.vtt 14KB
  163. 20. Machine Learning with R - Linear Regression/4. Linear Regression with R - Part 3.vtt 14KB
  164. 29. Machine Learning Project - Support Vector Machines/2. Support Vector Machines Project - Solutions Part 1.vtt 14KB
  165. 21. Machine Learning Project - Linear Regression/3. ML - Linear Regression Project - Solutions Part 2.vtt 14KB
  166. 06. Development Environment Overview/2. Course Notes.vtt 13KB
  167. 08. R Matrices/2. Creating a Matrix.vtt 13KB
  168. 29. Machine Learning Project - Support Vector Machines/3. Support Vector Machines Project - Solutions Part 2.vtt 13KB
  169. 14. Data Manipulation with R/3. Guide to Using Dplyr - Part 2.vtt 13KB
  170. 30. Machine Learning with R - K-means Clustering/2. K Means Clustering with R.vtt 13KB
  171. 21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.vtt 13KB
  172. 15. Data Visualization with R/7. Coordinates and Faceting.vtt 13KB
  173. 07. Introduction to R Basics/8. Vector Indexing and Slicing.vtt 13KB
  174. 25. Machine Learning Project - K Nearest Neighbors/2. K Nearest Neighbors Project Solutions.vtt 12KB
  175. 17. Interactive Visualizations with Plotly/1. Overview of Plotly and Interactive Visualizations.vtt 12KB
  176. 18. Capstone Data Project/1. Introduction to Capstone Project.vtt 11KB
  177. 09. R Data Frames/3. Data Frame Indexing and Selection.vtt 11KB
  178. 10. R Lists/1. List Basics.vtt 11KB
  179. 13. Advanced R Programming/2. Built-in R Features.vtt 11KB
  180. 34. Machine Learning Project - Neural Nets/2. Neural Nets Project - Solutions.vtt 11KB
  181. 09. R Data Frames/2. Data Frame Basics.vtt 11KB
  182. 15. Data Visualization with R/4. Barplots.vtt 10KB
  183. 08. R Matrices/6. Factor and Categorical Matrices.vtt 10KB
  184. 12. R Programming Basics/2. Logical Operators.vtt 10KB
  185. 15. Data Visualization with R/5. Boxplots.vtt 10KB
  186. 11. Data Input and Output with R/5. Web Scraping with R.vtt 9KB
  187. 15. Data Visualization with R/6. 2 Variable Plotting.vtt 9KB
  188. 12. R Programming Basics/6. While Loops.vtt 9KB
  189. 15. Data Visualization with R/1. Overview of ggplot2.vtt 9KB
  190. 07. Introduction to R Basics/11. R Basics Training Exercise - Solutions Walkthrough.vtt 9KB
  191. 03. Windows Installation Set-Up/1. Windows Installation Procedure.vtt 9KB
  192. 07. Introduction to R Basics/5. Vector Basics.vtt 9KB
  193. 08. R Matrices/5. Matrix Selection and Indexing.vtt 9KB
  194. 07. Introduction to R Basics/7. Comparison Operators.vtt 8KB
  195. 14. Data Manipulation with R/4. Pipe Operator.vtt 8KB
  196. 33. Machine Learning with R - Neural Nets/1. Introduction to Neural Nets.vtt 8KB
  197. 26. Machine Learning with R - Decision Trees and Random Forests/1. Introduction to Tree Methods.vtt 8KB
  198. 11. Data Input and Output with R/2. CSV Files with R.vtt 8KB
  199. 04. Mac OS Installation Set-Up/1. Mac OS Installation Procedure.vtt 8KB
  200. 20. Machine Learning with R - Linear Regression/1. Introduction to Linear Regression.vtt 7KB
  201. 15. Data Visualization with R/8. Themes.vtt 7KB
  202. 32. Machine Learning with R - Natural Language Processing/2. Natural Language Processing with R - Part 1.vtt 7KB
  203. 08. R Matrices/4. Matrix Operations.vtt 7KB
  204. 07. Introduction to R Basics/4. R Basic Data Types.vtt 7KB
  205. 07. Introduction to R Basics/3. Variables.vtt 7KB
  206. 24. Machine Learning with R - K Nearest Neighbors/1. Introduction to K Nearest Neighbors.vtt 6KB
  207. 27. Machine Learning Project - Decision Trees and Random Forests/3. Tree Methods Project Solutions - Part 2.vtt 6KB
  208. 30. Machine Learning with R - K-means Clustering/1. Introduction to K-Means Clustering.vtt 6KB
  209. 13. Advanced R Programming/5. Regular Expressions.vtt 6KB
  210. 07. Introduction to R Basics/2. Arithmetic in R.vtt 6KB
  211. 08. R Matrices/3. Matrix Arithmetic.vtt 6KB
  212. 35. Bonus Section - Discounts for Other Courses/1. Bonus Lecture Coupons.html 6KB
  213. 07. Introduction to R Basics/6. Vector Operations.vtt 6KB
  214. 32. Machine Learning with R - Natural Language Processing/1. Introduction to Natural Language Processing.vtt 6KB
  215. 28. Machine Learning with R - Support Vector Machines/1. Introduction to Support Vector Machines.vtt 6KB
  216. 01. Course Introduction/3. What is Data Science.vtt 5KB
  217. 25. Machine Learning Project - K Nearest Neighbors/1. Introduction K Nearest Neighbors Project.vtt 5KB
  218. 13. Advanced R Programming/4. Math Functions with R.vtt 4KB
  219. 16. Data Visualization Project/1. Data Visualization Project.vtt 4KB
  220. 15. Data Visualization with R/9. ggplot2 Exercises.vtt 4KB
  221. 07. Introduction to R Basics/1. Introduction to R Basics.vtt 4KB
  222. 01. Course Introduction/1. Introduction to Course.vtt 4KB
  223. 29. Machine Learning Project - Support Vector Machines/1. Introduction to SVM Project.vtt 4KB
  224. 12. R Programming Basics/9. Functions Training Exercise.vtt 3KB
  225. 34. Machine Learning Project - Neural Nets/1. Introduction to Neural Nets Project.vtt 3KB
  226. 07. Introduction to R Basics/10. R Basics Training Exercise.vtt 3KB
  227. 31. Machine Learning Project - K-means Clustering/1. Introduction to K Means Clustering Project.vtt 3KB
  228. 01. Course Introduction/2. Course Curriculum.vtt 3KB
  229. 07. Introduction to R Basics/9. Getting Help with R and RStudio.vtt 3KB
  230. 23. Machine Learning Project - Logistic Regression/1. Introduction to Logistic Regression Project.vtt 3KB
  231. 27. Machine Learning Project - Decision Trees and Random Forests/1. Introduction to Decision Trees and Random Forests Project.vtt 3KB
  232. 12. R Programming Basics/4. Conditional Statements Training Exercise.vtt 2KB
  233. 02. Course Best Practices/1. How to Get Help in the Course!.html 2KB
  234. 14. Data Manipulation with R/6. Dplyr Training Exercise.vtt 2KB
  235. 09. R Data Frames/6. Data Frame Training Exercise.vtt 2KB
  236. 05. Linux Installation/1. LinuxUnbuntu Installation Procedure.html 1KB
  237. 12. R Programming Basics/1. Introduction to Programming Basics.vtt 1KB
  238. 08. R Matrices/7. Matrix Training Exercise.vtt 1KB
  239. 13. Advanced R Programming/1. Introduction to Advanced R Programming.vtt 1KB
  240. 01. Course Introduction/4. Course FAQ.html 1KB
  241. 08. R Matrices/1. Introduction to R Matrices.vtt 1KB
  242. 09. R Data Frames/1. Introduction to R Data Frames.vtt 1022B
  243. 17. Interactive Visualizations with Plotly/2. Resources for Plotly and ggplot2.html 962B
  244. 14. Data Manipulation with R/1. Data Manipulation Overview.vtt 945B
  245. 11. Data Input and Output with R/1. Introduction to Data Input and Output with R.vtt 462B
  246. 06. Development Environment Overview/1. Development Environment Overview.vtt 451B
  247. 19. Introduction to Machine Learning with R/1. ISLR PDF.html 393B
  248. 02. Course Best Practices/3. Installation and Set-Up.html 335B
  249. 14. Data Manipulation with R/5. Quick note on Dpylr exercise.html 309B
  250. 02. Course Best Practices/2. Welcome to the Course..html 155B
  251. udemycoursedownloader.com.url 132B
  252. 08. R Matrices/4.1 Reference of Built-in Functions.html 117B
  253. Udemy Course downloader.txt 94B