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GetFreeCourses.Me-Udemy-Complete Machine Learning and Data Science Zero to Mastery

  • 收录时间:2020-02-15 09:45:19
  • 文件大小:13GB
  • 下载次数:94
  • 最近下载:2021-01-22 19:56:34
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文件列表

  1. 5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4 228MB
  2. 9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4 190MB
  3. 9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4 176MB
  4. 17. Career Advice + Extra Bits/9. CWD Git + Github.mp4 176MB
  5. 9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.mp4 176MB
  6. 17. Career Advice + Extra Bits/3. What If I Don_t Have Enough Experience.mp4 161MB
  7. 12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.mp4 159MB
  8. 9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.mp4 158MB
  9. 12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.mp4 146MB
  10. 5. Data Science Environment Setup/5. Mac Environment Setup.mp4 144MB
  11. 9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.mp4 143MB
  12. 12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.mp4 142MB
  13. 12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4 139MB
  14. 11. Milestone Project 1 Supervised Learning (Binary Classification)/9. Finding Patterns 3.mp4 138MB
  15. 12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.mp4 138MB
  16. 9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 137MB
  17. 9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.mp4 135MB
  18. 17. Career Advice + Extra Bits/11. Contributing To Open Source.mp4 130MB
  19. 11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.mp4 127MB
  20. 5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4 125MB
  21. 8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.mp4 124MB
  22. 9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.mp4 122MB
  23. 8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4 120MB
  24. 9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).mp4 119MB
  25. 17. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4 118MB
  26. 9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.mp4 117MB
  27. 9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.mp4 117MB
  28. 17. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4 113MB
  29. 11. Milestone Project 1 Supervised Learning (Binary Classification)/14. Tuning Hyperparameters.mp4 108MB
  30. 12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4 106MB
  31. 11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.mp4 106MB
  32. 6. Pandas Data Analysis/9. Manipulating Data.mp4 105MB
  33. 9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 105MB
  34. 18. Learn Python/1. What Is A Programming Language.mp4 105MB
  35. 11. Milestone Project 1 Supervised Learning (Binary Classification)/15. Tuning Hyperparameters 2.mp4 104MB
  36. 5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.mp4 104MB
  37. 12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.mp4 103MB
  38. 11. Milestone Project 1 Supervised Learning (Binary Classification)/13. TuningImproving Our Model.mp4 103MB
  39. 12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4 101MB
  40. 11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4 101MB
  41. 11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.mp4 100MB
  42. 8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4 99MB
  43. 11. Milestone Project 1 Supervised Learning (Binary Classification)/11. Choosing The Right Models.mp4 96MB
  44. 9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 96MB
  45. 9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.mp4 95MB
  46. 18. Learn Python/16. Variables.mp4 94MB
  47. 12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp4 93MB
  48. 18. Learn Python/2. Python Interpreter.mp4 93MB
  49. 8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.mp4 92MB
  50. 9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 91MB
  51. 7. NumPy/13. Exercise Nut Butter Store Sales.mp4 91MB
  52. 6. Pandas Data Analysis/11. Manipulating Data 3.mp4 91MB
  53. 9. Scikit-learn Creating Machine Learning Models/37. Improving A Machine Learning Model.mp4 91MB
  54. 9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4 88MB
  55. 9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).mp4 87MB
  56. 9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).mp4 87MB
  57. 9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data 2 (Regression).mp4 87MB
  58. 6. Pandas Data Analysis/10. Manipulating Data 2.mp4 87MB
  59. 8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 86MB
  60. 11. Milestone Project 1 Supervised Learning (Binary Classification)/21. Reviewing The Project.mp4 86MB
  61. 7. NumPy/16. Turn Images Into NumPy Arrays.mp4 86MB
  62. 12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.mp4 86MB
  63. 12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.mp4 86MB
  64. 7. NumPy/12. Dot Product vs Element Wise.mp4 84MB
  65. 12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.mp4 83MB
  66. 8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4 82MB
  67. 18. Learn Python/5. Python 2 vs Python 3.mp4 82MB
  68. 8. Matplotlib + Seaborn Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4 82MB
  69. 7. NumPy/8. Manipulating Arrays.mp4 81MB
  70. 13. Data Engineering/9. Optional OLTP Databases.mp4 80MB
  71. 11. Milestone Project 1 Supervised Learning (Binary Classification)/5. Getting Our Tools Ready.mp4 79MB
  72. 12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.mp4 79MB
  73. 12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.mp4 79MB
  74. 7. NumPy/4. NumPy DataTypes and Attributes.mp4 79MB
  75. 9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 4 (Confusion Matrix).mp4 78MB
  76. 9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4 75MB
  77. 8. Matplotlib + Seaborn Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4 75MB
  78. 18. Learn Python/10. Numbers.mp4 73MB
  79. 11. Milestone Project 1 Supervised Learning (Binary Classification)/10. Preparing Our Data For Machine Learning.mp4 73MB
  80. 11. Milestone Project 1 Supervised Learning (Binary Classification)/17. Evaluating Our Model.mp4 72MB
  81. 7. NumPy/7. Viewing Arrays and Matrices.mp4 71MB
  82. 9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Regression Model 1 (R2 Score).mp4 70MB
  83. 8. Matplotlib + Seaborn Plotting and Data Visualization/6. Histograms And Subplots.mp4 70MB
  84. 18. Learn Python/26. Built-In Functions + Methods.mp4 69MB
  85. 7. NumPy/9. Manipulating Arrays 2.mp4 68MB
  86. 5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.mp4 67MB
  87. 8. Matplotlib + Seaborn Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp4 67MB
  88. 12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.mp4 67MB
  89. 11. Milestone Project 1 Supervised Learning (Binary Classification)/6. Exploring Our Data.mp4 67MB
  90. 6. Pandas Data Analysis/13. How To Download The Course Assignments.mp4 67MB
  91. 7. NumPy/5. Creating NumPy Arrays.mp4 67MB
  92. 9. Scikit-learn Creating Machine Learning Models/20. Making Predictions With Our Model.mp4 67MB
  93. 9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 2 (ROC Curve).mp4 66MB
  94. 11. Milestone Project 1 Supervised Learning (Binary Classification)/19. Evaluating Our Model 3.mp4 65MB
  95. 18. Learn Python/48. Sets 2.mp4 64MB
  96. 18. Learn Python/3. How To Run Python Code.mp4 64MB
  97. 9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp4 64MB
  98. 9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 5 (Confusion Matrix).mp4 64MB
  99. 11. Milestone Project 1 Supervised Learning (Binary Classification)/7. Finding Patterns.mp4 63MB
  100. 11. Milestone Project 1 Supervised Learning (Binary Classification)/16. Tuning Hyperparameters 3.mp4 63MB
  101. 18. Learn Python/34. List Methods.mp4 62MB
  102. 3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.mp4 60MB
  103. 8. Matplotlib + Seaborn Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 60MB
  104. 18. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp4 60MB
  105. 8. Matplotlib + Seaborn Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4 57MB
  106. 9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model 2.mp4 57MB
  107. 9. Scikit-learn Creating Machine Learning Models/19. Fitting A Model To The Data.mp4 57MB
  108. 12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.mp4 56MB
  109. 11. Milestone Project 1 Supervised Learning (Binary Classification)/12. Experimenting With Machine Learning Models.mp4 55MB
  110. 9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 3 (MSE).mp4 55MB
  111. 9. Scikit-learn Creating Machine Learning Models/21. predict() vs predict_proba().mp4 54MB
  112. 7. NumPy/11. Reshape and Transpose.mp4 54MB
  113. 9. Scikit-learn Creating Machine Learning Models/42. Saving And Loading A Model.mp4 53MB
  114. 12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp4 52MB
  115. 7. NumPy/6. NumPy Random Seed.mp4 52MB
  116. 7. NumPy/10. Standard Deviation and Variance.mp4 51MB
  117. 18. Learn Python/30. Exercise Password Checker.mp4 51MB
  118. 9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 3 (ROC Curve).mp4 51MB
  119. 18. Learn Python/28. Exercise Type Conversion.mp4 50MB
  120. 18. Learn Python/32. List Slicing.mp4 50MB
  121. 8. Matplotlib + Seaborn Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 50MB
  122. 18. Learn Python/23. Formatted Strings.mp4 49MB
  123. 18. Learn Python/24. String Indexes.mp4 49MB
  124. 8. Matplotlib + Seaborn Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4 49MB
  125. 5. Data Science Environment Setup/7. Windows Environment Setup.mp4 48MB
  126. 18. Learn Python/4. Our First Python Program.mp4 47MB
  127. 9. Scikit-learn Creating Machine Learning Models/22. Making Predictions With Our Model (Regression).mp4 45MB
  128. 3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4 45MB
  129. 2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4 43MB
  130. 18. Learn Python/44. Dictionary Methods 2.mp4 42MB
  131. 13. Data Engineering/2. What Is Data.mp4 42MB
  132. 18. Learn Python/11. Math Functions.mp4 42MB
  133. 11. Milestone Project 1 Supervised Learning (Binary Classification)/18. Evaluating Our Model 2.mp4 42MB
  134. 1. Introduction/1. Course Outline.mp4 41MB
  135. 9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4 41MB
  136. 18. Learn Python/37. Common List Patterns.mp4 40MB
  137. 18. Learn Python/7. Learning Python.mp4 39MB
  138. 8. Matplotlib + Seaborn Plotting and Data Visualization/7. Subplots Option 2.mp4 38MB
  139. 5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 3.mp4 38MB
  140. 18. Learn Python/47. Sets.mp4 37MB
  141. 3. Machine Learning and Data Science Framework/7. Features In Data.mp4 37MB
  142. 11. Milestone Project 1 Supervised Learning (Binary Classification)/2. Project Overview.mp4 34MB
  143. 12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp4 33MB
  144. 7. NumPy/15. Sorting Arrays.mp4 33MB
  145. 18. Learn Python/40. Dictionaries.mp4 33MB
  146. 13. Data Engineering/7. Types Of Databases.mp4 33MB
  147. 8. Matplotlib + Seaborn Plotting and Data Visualization/2. Matplotlib Introduction.mp4 32MB
  148. 9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Classification Model 1 (Accuracy).mp4 31MB
  149. 18. Learn Python/19. Strings.mp4 31MB
  150. 5. Data Science Environment Setup/4. Conda Environments.mp4 31MB
  151. 2. Machine Learning 101/4. How Did We Get Here.mp4 31MB
  152. 3. Machine Learning and Data Science Framework/5. Types of Data.mp4 29MB
  153. 18. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp4 29MB
  154. 18. Learn Python/8. Python Data Types.mp4 29MB
  155. 18. Learn Python/36. List Methods 3.mp4 28MB
  156. 3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp4 28MB
  157. 6. Pandas Data Analysis/3. Pandas Introduction.mp4 27MB
  158. 18. Learn Python/35. List Methods 2.mp4 27MB
  159. 3. Machine Learning and Data Science Framework/13. Tools We Will Use.mp4 27MB
  160. 18. Learn Python/43. Dictionary Methods.mp4 27MB
  161. 7. NumPy/2. NumPy Introduction.mp4 27MB
  162. 18. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp4 27MB
  163. 7. NumPy/14. Comparison Operators.mp4 26MB
  164. 18. Learn Python/6. Exercise How Does Python Work.mp4 26MB
  165. 18. Learn Python/45. Tuples.mp4 26MB
  166. 2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 26MB
  167. 13. Data Engineering/5. What Is A Data Engineer 3.mp4 24MB
  168. 13. Data Engineering/4. What Is A Data Engineer 2.mp4 24MB
  169. 3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp4 23MB
  170. 3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.mp4 23MB
  171. 18. Learn Python/22. Escape Sequences.mp4 23MB
  172. 2. Machine Learning 101/6. Types of Machine Learning.mp4 23MB
  173. 19. Learn Python Part 2/43. Exercise Comprehensions.mp4 22MB
  174. 18. Learn Python/31. Lists.mp4 22MB
  175. 18. Learn Python/15. Optional bin() and complex.mp4 22MB
  176. 19. Learn Python Part 2/30. Exercise Functions.mp4 22MB
  177. 3. Machine Learning and Data Science Framework/12. Experimentation.mp4 21MB
  178. 18. Learn Python/25. Immutability.mp4 21MB
  179. 18. Learn Python/42. Dictionary Keys.mp4 20MB
  180. 2. Machine Learning 101/2. AIMachine LearningData Science.mp4 20MB
  181. 2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp4 19MB
  182. 5. Data Science Environment Setup/2. Introducing Our Tools.mp4 19MB
  183. 13. Data Engineering/13. Kafka and Stream Processing.mp4 19MB
  184. 18. Learn Python/33. Matrix.mp4 19MB
  185. 18. Learn Python/21. Type Conversion.mp4 19MB
  186. 3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp4 18MB
  187. 18. Learn Python/46. Tuples 2.mp4 17MB
  188. 2. Machine Learning 101/1. What Is Machine Learning.mp4 17MB
  189. 18. Learn Python/27. Booleans.mp4 17MB
  190. 9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp4 17MB
  191. 3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp4 16MB
  192. 17. Career Advice + Extra Bits/7. JTS Start With Why.mp4 15MB
  193. 18. Learn Python/18. Augmented Assignment Operator.mp4 15MB
  194. 13. Data Engineering/3. What Is A Data Engineer.mp4 15MB
  195. 13. Data Engineering/6. What Is A Data Engineer 4.mp4 15MB
  196. 18. Learn Python/13. Operator Precedence.mp4 14MB
  197. 18. Learn Python/38. List Unpacking.mp4 14MB
  198. 13. Data Engineering/1. Data Engineering Introduction.mp4 13MB
  199. 3. Machine Learning and Data Science Framework/1. Section Overview.mp4 13MB
  200. 7. NumPy/1. Section Overview.mp4 13MB
  201. 5. Data Science Environment Setup/3. What is Conda.mp4 12MB
  202. 9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp4 12MB
  203. 8. Matplotlib + Seaborn Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp4 12MB
  204. 3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp4 11MB
  205. 17. Career Advice + Extra Bits/6. JTS Learn to Learn.mp4 11MB
  206. 21. Where To Go From Here/2. Thank You.mp4 11MB
  207. 18. Learn Python/17. Expressions vs Statements.mp4 11MB
  208. 6. Pandas Data Analysis/1. Section Overview.mp4 11MB
  209. 11. Milestone Project 1 Supervised Learning (Binary Classification)/1. Section Overview.mp4 10MB
  210. 13. Data Engineering/11. Hadoop, HDFS and MapReduce.mp4 10MB
  211. 4. The 2 Paths/1. The 2 Paths.mp4 10MB
  212. 12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp4 9MB
  213. 8. Matplotlib + Seaborn Plotting and Data Visualization/1. Section Overview.mp4 9MB
  214. 1. Introduction/4. Your First Day.mp4 8MB
  215. 18. Learn Python/39. None.mp4 8MB
  216. 18. Learn Python/20. String Concatenation.mp4 7MB
  217. 7. NumPy/16.2 numpy-images.zip.zip 7MB
  218. 13. Data Engineering/12. Apache Spark and Apache Flink.mp4 6MB
  219. 2. Machine Learning 101/9. Section Review.mp4 3MB
  220. 5. Data Science Environment Setup/1. Section Overview.mp4 2MB
  221. 8. Matplotlib + Seaborn Plotting and Data Visualization/4.2 matplotlib-anatomy-of-a-plot-with-code.png.png 655KB
  222. 8. Matplotlib + Seaborn Plotting and Data Visualization/4.1 matplotlib-anatomy-of-a-plot.png.png 369KB
  223. 6. Pandas Data Analysis/10.1 pandas-anatomy-of-a-dataframe.png.png 333KB
  224. 6. Pandas Data Analysis/4.1 pandas-anatomy-of-a-dataframe.png.png 333KB
  225. 11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4.jpg 215KB
  226. 5. Data Science Environment Setup/3.4 conda-cheatsheet.pdf.pdf 201KB
  227. 9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.srt 32KB
  228. 5. Data Science Environment Setup/8. Windows Environment Setup 2.srt 32KB
  229. 9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.srt 31KB
  230. 6. Pandas Data Analysis/9.1 car-sales-extended-missing-data.csv.csv 30KB
  231. 9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.srt 26KB
  232. 9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.srt 26KB
  233. 5. Data Science Environment Setup/5. Mac Environment Setup.srt 24KB
  234. 9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt 23KB
  235. 9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.srt 23KB
  236. 5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.srt 22KB
  237. 11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.srt 22KB
  238. 11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.srt 22KB
  239. 12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.srt 22KB
  240. 12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.srt 22KB
  241. 9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.srt 21KB
  242. 17. Career Advice + Extra Bits/9. CWD Git + Github.srt 21KB
  243. 5. Data Science Environment Setup/6. Mac Environment Setup 2.srt 21KB
  244. 17. Career Advice + Extra Bits/3. What If I Don_t Have Enough Experience.srt 20KB
  245. 12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.srt 20KB
  246. 7. NumPy/4. NumPy DataTypes and Attributes.srt 19KB
  247. 11. Milestone Project 1 Supervised Learning (Binary Classification)/9. Finding Patterns 3.srt 19KB
  248. 9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.srt 19KB
  249. 17. Career Advice + Extra Bits/10. CWD Git + Github 2.srt 18KB
  250. 6. Pandas Data Analysis/9. Manipulating Data.srt 18KB
  251. 9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.srt 18KB
  252. 6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.srt 18KB
  253. 12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.srt 18KB
  254. 11. Milestone Project 1 Supervised Learning (Binary Classification)/13. TuningImproving Our Model.srt 18KB
  255. 12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.srt 17KB
  256. 9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).srt 17KB
  257. 17. Career Advice + Extra Bits/11. Contributing To Open Source.srt 17KB
  258. 9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).srt 17KB
  259. 9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.srt 17KB
  260. 7. NumPy/13. Exercise Nut Butter Store Sales.srt 17KB
  261. 9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.srt 17KB
  262. 12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.srt 17KB
  263. 6. Pandas Data Analysis/4. Series, Data Frames and CSVs.srt 17KB
  264. 11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.srt 17KB
  265. 9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.srt 16KB
  266. 7. NumPy/8. Manipulating Arrays.srt 16KB
  267. 9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.srt 16KB
  268. 12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.srt 16KB
  269. 8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.srt 16KB
  270. 18. Learn Python/16. Variables.srt 16KB
  271. 12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.srt 16KB
  272. 11. Milestone Project 1 Supervised Learning (Binary Classification)/14. Tuning Hyperparameters.srt 16KB
  273. 19. Learn Python Part 2/2. Conditional Logic.srt 16KB
  274. 7. NumPy/12. Dot Product vs Element Wise.srt 15KB
  275. 5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.srt 15KB
  276. 11. Milestone Project 1 Supervised Learning (Binary Classification)/17. Evaluating Our Model.srt 15KB
  277. 9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 4 (Confusion Matrix).srt 15KB
  278. 11. Milestone Project 1 Supervised Learning (Binary Classification)/15. Tuning Hyperparameters 2.srt 15KB
  279. 19. Learn Python Part 2/24. return.srt 15KB
  280. 8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.srt 15KB
  281. 9. Scikit-learn Creating Machine Learning Models/37. Improving A Machine Learning Model.srt 15KB
  282. 8. Matplotlib + Seaborn Plotting and Data Visualization/5. Scatter Plot And Bar Plot.srt 15KB
  283. 12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.srt 15KB
  284. 6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.srt 15KB
  285. 9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).srt 15KB
  286. 11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.srt 14KB
  287. 8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.srt 14KB
  288. 3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.srt 14KB
  289. 8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.srt 14KB
  290. 6. Pandas Data Analysis/10. Manipulating Data 2.srt 14KB
  291. 11. Milestone Project 1 Supervised Learning (Binary Classification)/21. Reviewing The Project.srt 14KB
  292. 6. Pandas Data Analysis/11. Manipulating Data 3.srt 14KB
  293. 8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.srt 14KB
  294. 6. Pandas Data Analysis/6. Describing Data with Pandas.srt 14KB
  295. 12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.srt 14KB
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  541. 12. Milestone Project 2 Supervised Learning (Time Series Data)/19.1 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208B
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  549. 11. Milestone Project 1 Supervised Learning (Binary Classification)/21.1 End-to-end Heart Disease Classification Notebook (with annotations).html 201B
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