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[FreeAllCourse.Com] Udemy - Complete Machine Learning and Data Science Zero to Mastery

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FreeAllCourse Com Udemy - Complete Machine Learning and Data Science Zero to Mastery

文件列表
  1. 1. Introduction/1. Course Outline.mp477.27MB
  2. 1. Introduction/4. Your First Day.mp427.92MB
  3. 11. Milestone Project 1 Supervised Learning (Classification)/1. Section Overview.mp410.19MB
  4. 11. Milestone Project 1 Supervised Learning (Classification)/10. Preparing Our Data For Machine Learning.mp472.6MB
  5. 11. Milestone Project 1 Supervised Learning (Classification)/11. Choosing The Right Models.mp496.42MB
  6. 11. Milestone Project 1 Supervised Learning (Classification)/12. Experimenting With Machine Learning Models.mp455.35MB
  7. 11. Milestone Project 1 Supervised Learning (Classification)/13. TuningImproving Our Model.mp4102.78MB
  8. 11. Milestone Project 1 Supervised Learning (Classification)/14. Tuning Hyperparameters.mp4108MB
  9. 11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters 2.mp4104.12MB
  10. 11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 3.mp463.01MB
  11. 11. Milestone Project 1 Supervised Learning (Classification)/17. Evaluating Our Model.mp471.6MB
  12. 11. Milestone Project 1 Supervised Learning (Classification)/18. Evaluating Our Model 2.mp441.53MB
  13. 11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model 3.mp464.84MB
  14. 11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.mp434.44MB
  15. 11. Milestone Project 1 Supervised Learning (Classification)/20. Finding The Most Important Features.mp4127.49MB
  16. 11. Milestone Project 1 Supervised Learning (Classification)/21. Reviewing The Project.mp486.14MB
  17. 11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.mp4100.76MB
  18. 11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.mp4105.5MB
  19. 11. Milestone Project 1 Supervised Learning (Classification)/5. Getting Our Tools Ready.mp479.36MB
  20. 11. Milestone Project 1 Supervised Learning (Classification)/6. Exploring Our Data.mp466.88MB
  21. 11. Milestone Project 1 Supervised Learning (Classification)/7. Finding Patterns.mp463.34MB
  22. 11. Milestone Project 1 Supervised Learning (Classification)/8. Finding Patterns 2.mp499.92MB
  23. 11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 3.mp4137.87MB
  24. 12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp48.96MB
  25. 12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.mp466.91MB
  26. 12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.mp455.52MB
  27. 12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.mp482.68MB
  28. 12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.mp4103.34MB
  29. 12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp493.47MB
  30. 12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.mp485.83MB
  31. 12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.mp479.29MB
  32. 12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4139.3MB
  33. 12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.mp479.21MB
  34. 12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.mp4142.3MB
  35. 12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp432.94MB
  36. 12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4101.27MB
  37. 12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.mp485.69MB
  38. 12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.mp4137.81MB
  39. 12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp452.04MB
  40. 12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.mp4159.14MB
  41. 12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.mp4146.17MB
  42. 12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4106.34MB
  43. 13. Data Engineering/1. Data Engineering Introduction.mp413.51MB
  44. 13. Data Engineering/11. Hadoop, HDFS and MapReduce.mp410.11MB
  45. 13. Data Engineering/12. Apache Spark and Apache Flink.mp45.77MB
  46. 13. Data Engineering/13. Kafka and Stream Processing.mp419.24MB
  47. 13. Data Engineering/2. What Is Data.mp442.22MB
  48. 13. Data Engineering/3. What Is A Data Engineer.mp415.16MB
  49. 13. Data Engineering/4. What Is A Data Engineer 2.mp424.23MB
  50. 13. Data Engineering/5. What Is A Data Engineer 3.mp424.29MB
  51. 13. Data Engineering/6. What Is A Data Engineer 4.mp414.93MB
  52. 13. Data Engineering/7. Types Of Databases.mp432.55MB
  53. 13. Data Engineering/9. Optional OLTP Databases.mp479.68MB
  54. 14. Neural Networks Deep Learning/1. Section Overview.mp412.2MB
  55. 14. Neural Networks Deep Learning/10. Optional TensorFlow 2.0 Default Issue.mp428.1MB
  56. 14. Neural Networks Deep Learning/11. Using A GPU.mp480.59MB
  57. 14. Neural Networks Deep Learning/12. Optional GPU and Google Colab.mp445.88MB
  58. 14. Neural Networks Deep Learning/13. Optional Reloading Colab Notebook.mp488.66MB
  59. 14. Neural Networks Deep Learning/14. Loading Our Data Labels.mp4114.82MB
  60. 14. Neural Networks Deep Learning/15. Preparing The Images.mp4133.89MB
  61. 14. Neural Networks Deep Learning/16. Turning Data Labels Into Numbers.mp4107.46MB
  62. 14. Neural Networks Deep Learning/17. Creating Our Own Validation Set.mp466.44MB
  63. 14. Neural Networks Deep Learning/18. Preprocess Images.mp490.1MB
  64. 14. Neural Networks Deep Learning/19. Preprocess Images 2.mp4105.07MB
  65. 14. Neural Networks Deep Learning/2. Deep Learning and Unstructured Data.mp4102.04MB
  66. 14. Neural Networks Deep Learning/20. Turning Data Into Batches.mp487.77MB
  67. 14. Neural Networks Deep Learning/21. Turning Data Into Batches 2.mp4149.38MB
  68. 14. Neural Networks Deep Learning/22. Visualizing Our Data.mp4121.99MB
  69. 14. Neural Networks Deep Learning/23. Preparing Our Inputs and Outputs.mp450.07MB
  70. 14. Neural Networks Deep Learning/25. Building A Deep Learning Model.mp4121.85MB
  71. 14. Neural Networks Deep Learning/26. Building A Deep Learning Model 2.mp4105.9MB
  72. 14. Neural Networks Deep Learning/27. Building A Deep Learning Model 3.mp4105.92MB
  73. 14. Neural Networks Deep Learning/28. Building A Deep Learning Model 4.mp486.3MB
  74. 14. Neural Networks Deep Learning/29. Summarizing Our Model.mp445.44MB
  75. 14. Neural Networks Deep Learning/30. Evaluating Our Model.mp479.29MB
  76. 14. Neural Networks Deep Learning/31. Preventing Overfitting.mp436.51MB
  77. 14. Neural Networks Deep Learning/32. Training Your Deep Neural Network.mp4166.6MB
  78. 14. Neural Networks Deep Learning/33. Evaluating Performance With TensorBoard.mp474.18MB
  79. 14. Neural Networks Deep Learning/34. Make And Transform Predictions.mp4154.98MB
  80. 14. Neural Networks Deep Learning/35. Transform Predictions To Text.mp4129.87MB
  81. 14. Neural Networks Deep Learning/36. Visualizing Model Predictions.mp4119.31MB
  82. 14. Neural Networks Deep Learning/37. Visualizing And Evaluate Model Predictions 2.mp4143.78MB
  83. 14. Neural Networks Deep Learning/38. Visualizing And Evaluate Model Predictions 3.mp4113.21MB
  84. 14. Neural Networks Deep Learning/39. Saving And Loading A Trained Model.mp4126.98MB
  85. 14. Neural Networks Deep Learning/4. Setting Up Google Colab.mp474.24MB
  86. 14. Neural Networks Deep Learning/40. Training Model On Full Dataset.mp4139.82MB
  87. 14. Neural Networks Deep Learning/41. Making Predictions On Test Images.mp4140.83MB
  88. 14. Neural Networks Deep Learning/42. Submitting Model to Kaggle.mp4121.34MB
  89. 14. Neural Networks Deep Learning/43. Making Predictions On Our Images.mp4119.24MB
  90. 14. Neural Networks Deep Learning/5. Google Colab Workspace.mp439.63MB
  91. 14. Neural Networks Deep Learning/6. Uploading Project Data.mp451.98MB
  92. 14. Neural Networks Deep Learning/7. Setting Up Our Data.mp442.26MB
  93. 14. Neural Networks Deep Learning/8. Setting Up Our Data 2.mp420.88MB
  94. 14. Neural Networks Deep Learning/9. Importing TensorFlow 2.mp4116.76MB
  95. 15. Storytelling + Communication How To Present Your Work/1. Section Overview.mp410.93MB
  96. 15. Storytelling + Communication How To Present Your Work/2. Communicating Your Work.mp420.2MB
  97. 15. Storytelling + Communication How To Present Your Work/3. Communicating With Managers.mp418.39MB
  98. 15. Storytelling + Communication How To Present Your Work/4. Communicating With Co-Workers.mp418.99MB
  99. 15. Storytelling + Communication How To Present Your Work/5. Weekend Project Principle.mp423.58MB
  100. 15. Storytelling + Communication How To Present Your Work/6. Communicating With Outside World.mp414.53MB
  101. 15. Storytelling + Communication How To Present Your Work/7. Storytelling.mp412.03MB
  102. 16. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4118.35MB
  103. 16. Career Advice + Extra Bits/11. Contributing To Open Source.mp4130.25MB
  104. 16. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4113.04MB
  105. 16. Career Advice + Extra Bits/3. What If I Don't Have Enough Experience.mp4160.95MB
  106. 16. Career Advice + Extra Bits/6. JTS Learn to Learn.mp411.15MB
  107. 16. Career Advice + Extra Bits/7. JTS Start With Why.mp415.43MB
  108. 16. Career Advice + Extra Bits/9. CWD Git + Github.mp4176.11MB
  109. 17. Learn Python/1. What Is A Programming Language.mp4104.77MB
  110. 17. Learn Python/10. Numbers.mp472.71MB
  111. 17. Learn Python/11. Math Functions.mp441.82MB
  112. 17. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp459.71MB
  113. 17. Learn Python/13. Operator Precedence.mp414.42MB
  114. 17. Learn Python/15. Optional bin() and complex.mp421.91MB
  115. 17. Learn Python/16. Variables.mp493.56MB
  116. 17. Learn Python/17. Expressions vs Statements.mp410.97MB
  117. 17. Learn Python/18. Augmented Assignment Operator.mp415.33MB
  118. 17. Learn Python/19. Strings.mp430.98MB
  119. 17. Learn Python/2. Python Interpreter.mp493.47MB
  120. 17. Learn Python/20. String Concatenation.mp47.34MB
  121. 17. Learn Python/21. Type Conversion.mp419MB
  122. 17. Learn Python/22. Escape Sequences.mp423.16MB
  123. 17. Learn Python/23. Formatted Strings.mp449.25MB
  124. 17. Learn Python/24. String Indexes.mp449.15MB
  125. 17. Learn Python/25. Immutability.mp420.81MB
  126. 17. Learn Python/26. Built-In Functions + Methods.mp469.39MB
  127. 17. Learn Python/27. Booleans.mp416.56MB
  128. 17. Learn Python/28. Exercise Type Conversion.mp450.34MB
  129. 17. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp429.25MB
  130. 17. Learn Python/3. How To Run Python Code.mp463.9MB
  131. 17. Learn Python/30. Exercise Password Checker.mp451.09MB
  132. 17. Learn Python/31. Lists.mp421.96MB
  133. 17. Learn Python/32. List Slicing.mp449.86MB
  134. 17. Learn Python/33. Matrix.mp419.15MB
  135. 17. Learn Python/34. List Methods.mp461.75MB
  136. 17. Learn Python/35. List Methods 2.mp427.4MB
  137. 17. Learn Python/36. List Methods 3.mp427.66MB
  138. 17. Learn Python/37. Common List Patterns.mp440.46MB
  139. 17. Learn Python/38. List Unpacking.mp413.86MB
  140. 17. Learn Python/39. None.mp47.93MB
  141. 17. Learn Python/4. Our First Python Program.mp447.2MB
  142. 17. Learn Python/40. Dictionaries.mp432.7MB
  143. 17. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp426.63MB
  144. 17. Learn Python/42. Dictionary Keys.mp420.38MB
  145. 17. Learn Python/43. Dictionary Methods.mp427.16MB
  146. 17. Learn Python/44. Dictionary Methods 2.mp442.39MB
  147. 17. Learn Python/45. Tuples.mp425.65MB
  148. 17. Learn Python/46. Tuples 2.mp416.99MB
  149. 17. Learn Python/47. Sets.mp436.98MB
  150. 17. Learn Python/48. Sets 2.mp464.26MB
  151. 17. Learn Python/5. Python 2 vs Python 3.mp482.14MB
  152. 17. Learn Python/6. Exercise How Does Python Work.mp425.96MB
  153. 17. Learn Python/7. Learning Python.mp438.52MB
  154. 17. Learn Python/8. Python Data Types.mp428.85MB
  155. 18. Learn Python Part 2/1. Breaking The Flow.mp420.34MB
  156. 18. Learn Python Part 2/10. For Loops.mp434.31MB
  157. 18. Learn Python Part 2/11. Iterables.mp443.2MB
  158. 18. Learn Python Part 2/12. Exercise Tricky Counter.mp416.4MB
  159. 18. Learn Python Part 2/13. range().mp428.33MB
  160. 18. Learn Python Part 2/14. enumerate().mp424.8MB
  161. 18. Learn Python Part 2/15. While Loops.mp428.32MB
  162. 18. Learn Python Part 2/16. While Loops 2.mp425.93MB
  163. 18. Learn Python Part 2/17. break, continue, pass.mp422.21MB
  164. 18. Learn Python Part 2/18. Our First GUI.mp449.63MB
  165. 18. Learn Python Part 2/19. DEVELOPER FUNDAMENTALS IV.mp450.22MB
  166. 18. Learn Python Part 2/2. Conditional Logic.mp474.58MB
  167. 18. Learn Python Part 2/20. Exercise Find Duplicates.mp420.26MB
  168. 18. Learn Python Part 2/21. Functions.mp448.6MB
  169. 18. Learn Python Part 2/22. Parameters and Arguments.mp423.15MB
  170. 18. Learn Python Part 2/23. Default Parameters and Keyword Arguments.mp438.14MB
  171. 18. Learn Python Part 2/24. return.mp463.04MB
  172. 18. Learn Python Part 2/26. Methods vs Functions.mp430.69MB
  173. 18. Learn Python Part 2/27. Docstrings.mp417.34MB
  174. 18. Learn Python Part 2/28. Clean Code.mp419.67MB
  175. 18. Learn Python Part 2/29. args and kwargs.mp443.02MB
  176. 18. Learn Python Part 2/3. Indentation In Python.mp428.02MB
  177. 18. Learn Python Part 2/30. Exercise Functions.mp421.85MB
  178. 18. Learn Python Part 2/31. Scope.mp420.15MB
  179. 18. Learn Python Part 2/32. Scope Rules.mp437.68MB
  180. 18. Learn Python Part 2/33. global Keyword.mp436.5MB
  181. 18. Learn Python Part 2/34. nonlocal Keyword.mp418.25MB
  182. 18. Learn Python Part 2/35. Why Do We Need Scope.mp419.18MB
  183. 18. Learn Python Part 2/36. Pure Functions.mp467.36MB
  184. 18. Learn Python Part 2/37. map().mp438.38MB
  185. 18. Learn Python Part 2/38. filter().mp423.55MB
  186. 18. Learn Python Part 2/39. zip().mp421.27MB
  187. 18. Learn Python Part 2/4. Truthy vs Falsey.mp442.82MB
  188. 18. Learn Python Part 2/40. reduce().mp452.27MB
  189. 18. Learn Python Part 2/41. List Comprehensions.mp453.34MB
  190. 18. Learn Python Part 2/42. Set Comprehensions.mp435.37MB
  191. 18. Learn Python Part 2/43. Exercise Comprehensions.mp421.96MB
  192. 18. Learn Python Part 2/45. Modules in Python.mp482.18MB
  193. 18. Learn Python Part 2/47. Optional PyCharm.mp453.06MB
  194. 18. Learn Python Part 2/48. Packages in Python.mp472.42MB
  195. 18. Learn Python Part 2/49. Different Ways To Import.mp447.96MB
  196. 18. Learn Python Part 2/5. Ternary Operator.mp419.7MB
  197. 18. Learn Python Part 2/6. Short Circuiting.mp419.39MB
  198. 18. Learn Python Part 2/7. Logical Operators.mp428.33MB
  199. 18. Learn Python Part 2/8. Exercise Logical Operators.mp446.62MB
  200. 18. Learn Python Part 2/9. is vs ==.mp433.57MB
  201. 2. Machine Learning 101/1. What Is Machine Learning.mp428.33MB
  202. 2. Machine Learning 101/2. AIMachine LearningData Science.mp419.67MB
  203. 2. Machine Learning 101/3. Exercise Machine Learning Playground.mp442.59MB
  204. 2. Machine Learning 101/4. How Did We Get Here.mp430.5MB
  205. 2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp419.43MB
  206. 2. Machine Learning 101/6. Types of Machine Learning.mp422.75MB
  207. 2. Machine Learning 101/8. What Is Machine Learning Round 2.mp425.51MB
  208. 2. Machine Learning 101/9. Section Review.mp45.57MB
  209. 20. Where To Go From Here/2. Thank You.mp411.12MB
  210. 3. Machine Learning and Data Science Framework/1. Section Overview.mp413.36MB
  211. 3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp415.99MB
  212. 3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp444.88MB
  213. 3. Machine Learning and Data Science Framework/12. Experimentation.mp421.33MB
  214. 3. Machine Learning and Data Science Framework/13. Tools We Will Use.mp427.34MB
  215. 3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp411.39MB
  216. 3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp423.46MB
  217. 3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.mp460.5MB
  218. 3. Machine Learning and Data Science Framework/5. Types of Data.mp429.32MB
  219. 3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp417.75MB
  220. 3. Machine Learning and Data Science Framework/7. Features In Data.mp436.78MB
  221. 3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp427.52MB
  222. 3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.mp423.25MB
  223. 4. The 2 Paths/1. The 2 Paths.mp49.76MB
  224. 5. Data Science Environment Setup/1. Section Overview.mp46.03MB
  225. 5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough.mp467.35MB
  226. 5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 2.mp4103.9MB
  227. 5. Data Science Environment Setup/13. Jupyter Notebook Walkthrough 3.mp471.42MB
  228. 5. Data Science Environment Setup/2. Introducing Our Tools.mp419.3MB
  229. 5. Data Science Environment Setup/3. What is Conda.mp412.48MB
  230. 5. Data Science Environment Setup/4. Conda Environments.mp430.56MB
  231. 5. Data Science Environment Setup/5. Mac Environment Setup.mp4144.39MB
  232. 5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4125.46MB
  233. 5. Data Science Environment Setup/7. Windows Environment Setup.mp447.92MB
  234. 5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4227.6MB
  235. 6. Pandas Data Analysis/1. Section Overview.mp410.88MB
  236. 6. Pandas Data Analysis/10. Manipulating Data 2.mp486.53MB
  237. 6. Pandas Data Analysis/11. Manipulating Data 3.mp491.02MB
  238. 6. Pandas Data Analysis/13. How To Download The Course Assignments.mp466.78MB
  239. 6. Pandas Data Analysis/3. Pandas Introduction.mp427.44MB
  240. 6. Pandas Data Analysis/4. Series, Data Frames and CSVs.mp495.37MB
  241. 6. Pandas Data Analysis/6. Describing Data with Pandas.mp475.56MB
  242. 6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.mp472.35MB
  243. 6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.mp4106.5MB
  244. 6. Pandas Data Analysis/9. Manipulating Data.mp4104.99MB
  245. 7. NumPy/1. Section Overview.mp413.32MB
  246. 7. NumPy/10. Standard Deviation and Variance.mp451.16MB
  247. 7. NumPy/11. Reshape and Transpose.mp453.53MB
  248. 7. NumPy/12. Dot Product vs Element Wise.mp483.93MB
  249. 7. NumPy/13. Exercise Nut Butter Store Sales.mp491.32MB
  250. 7. NumPy/14. Comparison Operators.mp426.37MB
  251. 7. NumPy/15. Sorting Arrays.mp432.83MB
  252. 7. NumPy/16. Turn Images Into NumPy Arrays.mp485.91MB
  253. 7. NumPy/2. NumPy Introduction.mp426.84MB
  254. 7. NumPy/4. NumPy DataTypes and Attributes.mp478.99MB
  255. 7. NumPy/5. Creating NumPy Arrays.mp466.77MB
  256. 7. NumPy/6. NumPy Random Seed.mp451.92MB
  257. 7. NumPy/7. Viewing Arrays and Matrices.mp470.64MB
  258. 7. NumPy/8. Manipulating Arrays.mp480.65MB
  259. 7. NumPy/9. Manipulating Arrays 2.mp467.9MB
  260. 8. Matplotlib Plotting and Data Visualization/1. Section Overview.mp48.6MB
  261. 8. Matplotlib Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp498.8MB
  262. 8. Matplotlib Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp474.71MB
  263. 8. Matplotlib Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp449MB
  264. 8. Matplotlib Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp456.96MB
  265. 8. Matplotlib Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp482.04MB
  266. 8. Matplotlib Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4119.75MB
  267. 8. Matplotlib Plotting and Data Visualization/17. Customizing Your Plots.mp492.21MB
  268. 8. Matplotlib Plotting and Data Visualization/18. Customizing Your Plots 2.mp4123.6MB
  269. 8. Matplotlib Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp449.52MB
  270. 8. Matplotlib Plotting and Data Visualization/2. Matplotlib Introduction.mp431.51MB
  271. 8. Matplotlib Plotting and Data Visualization/3. Importing And Using Matplotlib.mp486.45MB
  272. 8. Matplotlib Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp482.15MB
  273. 8. Matplotlib Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp467.03MB
  274. 8. Matplotlib Plotting and Data Visualization/6. Histograms And Subplots.mp469.75MB
  275. 8. Matplotlib Plotting and Data Visualization/7. Subplots Option 2.mp438.09MB
  276. 8. Matplotlib Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp412.26MB
  277. 8. Matplotlib Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp460.35MB
  278. 9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp412.46MB
  279. 9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp416.53MB
  280. 9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.mp4135.02MB
  281. 9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.mp4104.84MB
  282. 9. Scikit-learn Creating Machine Learning Models/14. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4136.89MB
  283. 9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data.mp4143.26MB
  284. 9. Scikit-learn Creating Machine Learning Models/16. Choosing The Right Model For Your Data 2 (Regression).mp486.92MB
  285. 9. Scikit-learn Creating Machine Learning Models/18. Quick Tip How ML Algorithms Work.mp411.06MB
  286. 9. Scikit-learn Creating Machine Learning Models/19. Choosing The Right Model For Your Data 3 (Classification).mp4118.85MB
  287. 9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp440.63MB
  288. 9. Scikit-learn Creating Machine Learning Models/20. Fitting A Model To The Data.mp456.56MB
  289. 9. Scikit-learn Creating Machine Learning Models/21. Making Predictions With Our Model.mp466.5MB
  290. 9. Scikit-learn Creating Machine Learning Models/22. predict() vs predict_proba().mp454.33MB
  291. 9. Scikit-learn Creating Machine Learning Models/23. Making Predictions With Our Model (Regression).mp444.91MB
  292. 9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model (Score).mp487.13MB
  293. 9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Machine Learning Model 2 (Cross Validation).mp495.97MB
  294. 9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 1 (Accuracy).mp431.41MB
  295. 9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 2 (ROC Curve).mp466.04MB
  296. 9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 3 (ROC Curve).mp450.61MB
  297. 9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 4 (Confusion Matrix).mp477.72MB
  298. 9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 5 (Confusion Matrix).mp463.59MB
  299. 9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Classification Model 6 (Classification Report).mp487.24MB
  300. 9. Scikit-learn Creating Machine Learning Models/32. Evaluating A Regression Model 1 (R2 Score).mp470.39MB
  301. 9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 2 (MAE).mp428.52MB
  302. 9. Scikit-learn Creating Machine Learning Models/34. Evaluating A Regression Model 3 (MSE).mp454.9MB
  303. 9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Cross Validation and Scoring Parameter.mp491.49MB
  304. 9. Scikit-learn Creating Machine Learning Models/37. Evaluating A Model With Scikit-learn Functions.mp494.82MB
  305. 9. Scikit-learn Creating Machine Learning Models/38. Improving A Machine Learning Model.mp490.93MB
  306. 9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters.mp4175.56MB
  307. 9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp488.27MB
  308. 9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 2.mp4116.77MB
  309. 9. Scikit-learn Creating Machine Learning Models/41. Tuning Hyperparameters 3.mp4121.76MB
  310. 9. Scikit-learn Creating Machine Learning Models/42. Quick Tip Correlation Analysis.mp416.92MB
  311. 9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model.mp452.6MB
  312. 9. Scikit-learn Creating Machine Learning Models/44. Saving And Loading A Model 2.mp456.77MB
  313. 9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together.mp4158.35MB
  314. 9. Scikit-learn Creating Machine Learning Models/46. Putting It All Together 2.mp4116.85MB
  315. 9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp475.13MB
  316. 9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4190.19MB
  317. 9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4176.13MB
  318. 9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp463.66MB
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