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Урок 1. 00:06:00Course Outline
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Урок 2. 00:03:49Your First Day
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Урок 3. 00:06:53What Is Machine Learning?
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Урок 4. 00:04:52AI/Machine Learning/Data Science
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Урок 5. 00:06:17Exercise: Machine Learning Playground
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Урок 6. 00:06:04How Did We Get Here?
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Урок 7. 00:04:25Exercise: YouTube Recommendation Engine
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Урок 8. 00:04:42Types of Machine Learning
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Урок 9. 00:04:45What Is Machine Learning? Round 2
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Урок 10. 00:01:49Section Review
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Урок 11. 00:03:09Section Overview
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Урок 12. 00:02:39Introducing Our Framework
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Урок 13. 00:05:006 Step Machine Learning Framework
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Урок 14. 00:10:33Types of Machine Learning Problems
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Урок 15. 00:04:51Types of Data
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Урок 16. 00:03:32Types of Evaluation
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Урок 17. 00:05:23Features In Data
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Урок 18. 00:05:59Modelling - Splitting Data
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Урок 19. 00:04:36Modelling - Picking the Model
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Урок 20. 00:03:18Modelling - Tuning
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Урок 21. 00:09:33Modelling - Comparison
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Урок 22. 00:03:36Experimentation
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Урок 23. 00:04:01Tools We Will Use
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Урок 24. 00:03:28The 2 Paths
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Урок 25. 00:01:10Section Overview
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Урок 26. 00:03:29Introducing Our Tools
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Урок 27. 00:02:36What is Conda?
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Урок 28. 00:04:31Conda Environments
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Урок 29. 00:17:27Mac Environment Setup
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Урок 30. 00:14:12Mac Environment Setup 2
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Урок 31. 00:05:18Windows Environment Setup
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Урок 32. 00:23:18Windows Environment Setup 2
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Урок 33. 00:10:21Jupyter Notebook Walkthrough
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Урок 34. 00:16:18Jupyter Notebook Walkthrough 2
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Урок 35. 00:08:11Jupyter Notebook Walkthrough 3
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Урок 36. 00:02:28Section Overview
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Урок 37. 00:04:30Pandas Introduction
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Урок 38. 00:13:22Series, Data Frames and CSVs
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Урок 39. 00:09:49Describing Data with Pandas
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Урок 40. 00:11:09Selecting and Viewing Data with Pandas
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Урок 41. 00:13:07Selecting and Viewing Data with Pandas Part 2
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Урок 42. 00:13:57Manipulating Data
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Урок 43. 00:09:57Manipulating Data 2
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Урок 44. 00:10:13Manipulating Data 3
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Урок 45. 00:07:44How To Download The Course Assignments
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Урок 46. 00:02:41Section Overview
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Урок 47. 00:05:18NumPy Introduction
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Урок 48. 00:14:06NumPy DataTypes and Attributes
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Урок 49. 00:09:23Creating NumPy Arrays
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Урок 50. 00:07:18NumPy Random Seed
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Урок 51. 00:09:36Viewing Arrays and Matrices
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Урок 52. 00:11:32Manipulating Arrays
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Урок 53. 00:09:45Manipulating Arrays 2
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Урок 54. 00:07:11Standard Deviation and Variance
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Урок 55. 00:07:27Reshape and Transpose
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Урок 56. 00:11:46Dot Product vs Element Wise
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Урок 57. 00:13:05Exercise: Nut Butter Store Sales
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Урок 58. 00:03:34Comparison Operators
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Урок 59. 00:06:20Sorting Arrays
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Урок 60. 00:07:38Turn Images Into NumPy Arrays
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Урок 61. 00:01:51Section Overview
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Урок 62. 00:05:17Matplotlib Introduction
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Урок 63. 00:11:37Importing And Using Matplotlib
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Урок 64. 00:09:20Anatomy Of A Matplotlib Figure
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Урок 65. 00:10:10Scatter Plot And Bar Plot
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Урок 66. 00:08:41Histograms And Subplots
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Урок 67. 00:04:16Subplots Option 2
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Урок 68. 00:01:49Quick Tip: Data Visualizations
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Урок 69. 00:05:59Plotting From Pandas DataFrames
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Урок 70. 00:10:34Plotting From Pandas DataFrames 2
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Урок 71. 00:08:33Plotting from Pandas DataFrames 3
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Урок 72. 00:06:37Plotting from Pandas DataFrames 4
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Урок 73. 00:08:29Plotting from Pandas DataFrames 5
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Урок 74. 00:08:28Plotting from Pandas DataFrames 6
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Урок 75. 00:11:21Plotting from Pandas DataFrames 7
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Урок 76. 00:10:10Customizing Your Plots
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Урок 77. 00:09:42Customizing Your Plots 2
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Урок 78. 00:04:15Saving And Sharing Your Plots
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Урок 79. 00:02:30Section Overview
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Урок 80. 00:06:42Scikit-learn Introduction
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Урок 81. 00:05:41Refresher: What Is Machine Learning?
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Урок 82. 00:06:13Scikit-learn Cheatsheet
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Урок 83. 00:23:15Typical scikit-learn Workflow
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Урок 84. 00:18:58Optional: Debugging Warnings In Jupyter
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Урок 85. 00:08:38Getting Your Data Ready: Splitting Your Data
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Урок 86. 00:05:04Quick Tip: Clean, Transform, Reduce
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Урок 87. 00:16:55Getting Your Data Ready: Convert Data To Numbers
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Урок 88. 00:12:23Getting Your Data Ready: Handling Missing Values With Pandas
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Урок 89. 00:17:30Getting Your Data Ready: Handling Missing Values With Scikit-learn
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Урок 90. 00:14:55Choosing The Right Model For Your Data
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Урок 91. 00:08:42Choosing The Right Model For Your Data 2 (Regression)
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Урок 92. 00:01:26Quick Tip: How ML Algorithms Work
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Урок 93. 00:12:46Choosing The Right Model For Your Data 3 (Classification)
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Урок 94. 00:06:46Fitting A Model To The Data
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Урок 95. 00:08:25Making Predictions With Our Model
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Урок 96. 00:08:34predict() vs predict_proba()
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Урок 97. 00:06:50Making Predictions With Our Model (Regression)
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Урок 98. 00:08:58Evaluating A Machine Learning Model (Score)
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Урок 99. 00:13:17Evaluating A Machine Learning Model 2 (Cross Validation)
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Урок 100. 00:04:47Evaluating A Classification Model 1 (Accuracy)
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Урок 101. 00:09:05Evaluating A Classification Model 2 (ROC Curve)
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Урок 102. 00:07:45Evaluating A Classification Model 3 (ROC Curve)
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Урок 103. 00:11:02Evaluating A Classification Model 4 (Confusion Matrix)
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Урок 104. 00:08:08Evaluating A Classification Model 5 (Confusion Matrix)
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Урок 105. 00:10:17Evaluating A Classification Model 6 (Classification Report)
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Урок 106. 00:09:13Evaluating A Regression Model 1 (R2 Score)
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Урок 107. 00:04:18Evaluating A Regression Model 2 (MAE)
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Урок 108. 00:06:35Evaluating A Regression Model 3 (MSE)
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Урок 109. 00:14:05Evaluating A Model With Cross Validation and Scoring Parameter
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Урок 110. 00:12:15Evaluating A Model With Scikit-learn Functions
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Урок 111. 00:11:17Improving A Machine Learning Model
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Урок 112. 00:23:16Tuning Hyperparameters
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Урок 113. 00:14:24Tuning Hyperparameters 2
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Урок 114. 00:15:00Tuning Hyperparameters 3
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Урок 115. 00:02:29Quick Tip: Correlation Analysis
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Урок 116. 00:07:29Saving And Loading A Model
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Урок 117. 00:06:21Saving And Loading A Model 2
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Урок 118. 00:20:20Putting It All Together
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Урок 119. 00:11:35Putting It All Together 2
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Урок 120. 00:02:10Section Overview
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Урок 121. 00:06:10Project Overview
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Урок 122. 00:10:59Project Environment Setup
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Урок 123. 00:12:07Step 1~4 Framework Setup
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Урок 124. 00:09:05Getting Our Tools Ready
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Урок 125. 00:08:34Exploring Our Data
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Урок 126. 00:10:03Finding Patterns
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Урок 127. 00:16:48Finding Patterns 2
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Урок 128. 00:13:37Finding Patterns 3
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Урок 129. 00:08:52Preparing Our Data For Machine Learning
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Урок 130. 00:10:16Choosing The Right Models
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Урок 131. 00:06:32Experimenting With Machine Learning Models
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Урок 132. 00:13:50Tuning/Improving Our Model
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Урок 133. 00:11:28Tuning Hyperparameters
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Урок 134. 00:11:50Tuning Hyperparameters 2
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Урок 135. 00:07:07Tuning Hyperparameters 3
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Урок 136. 00:11:00Evaluating Our Model
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Урок 137. 00:05:55Evaluating Our Model 2
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Урок 138. 00:08:50Evaluating Our Model 3
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Урок 139. 00:16:08Finding The Most Important Features
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Урок 140. 00:09:14Reviewing The Project
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Урок 141. 00:01:08Section Overview
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Урок 142. 00:04:25Project Overview
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Урок 143. 00:10:53Project Environment Setup
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Урок 144. 00:08:37Step 1~4 Framework Setup
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Урок 145. 00:14:17Exploring Our Data
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Урок 146. 00:06:17Exploring Our Data 2
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Урок 147. 00:15:25Feature Engineering
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Урок 148. 00:15:39Turning Data Into Numbers
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Урок 149. 00:12:50Filling Missing Numerical Values
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Урок 150. 00:08:28Filling Missing Categorical Values
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Урок 151. 00:07:17Fitting A Machine Learning Model
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Урок 152. 00:10:01Splitting Data
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Урок 153. 00:11:14Custom Evaluation Function
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Урок 154. 00:10:37Reducing Data
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Урок 155. 00:09:33RandomizedSearchCV
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Урок 156. 00:08:12Improving Hyperparameters
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Урок 157. 00:13:16Preproccessing Our Data
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Урок 158. 00:09:18Making Predictions
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Урок 159. 00:13:51Feature Importance
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Урок 160. 00:03:24Data Engineering Introduction
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Урок 161. 00:06:43What Is Data?
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Урок 162. 00:04:21What Is A Data Engineer?
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Урок 163. 00:05:36What Is A Data Engineer 2?
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Урок 164. 00:05:04What Is A Data Engineer 3?
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Урок 165. 00:03:23What Is A Data Engineer 4?
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Урок 166. 00:06:51Types Of Databases
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Урок 167. 00:10:55Optional: OLTP Databases
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Урок 168. 00:04:23Hadoop, HDFS and MapReduce
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Урок 169. 00:02:08Apache Spark and Apache Flink
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Урок 170. 00:04:34Kafka and Stream Processing
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Урок 171. 00:02:07Section Overview
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Урок 172. 00:13:37Deep Learning and Unstructured Data
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Урок 173. 00:07:18Setting Up Google Colab
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Урок 174. 00:04:24Google Colab Workspace
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Урок 175. 00:06:53Uploading Project Data
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Урок 176. 00:04:41Setting Up Our Data
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Урок 177. 00:01:33Setting Up Our Data 2
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Урок 178. 00:12:44Importing TensorFlow 2
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Урок 179. 00:03:39Optional: TensorFlow 2.0 Default Issue
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Урок 180. 00:09:00Using A GPU
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Урок 181. 00:04:28Optional: GPU and Google Colab
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Урок 182. 00:06:50Optional: Reloading Colab Notebook
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Урок 183. 00:12:05Loading Our Data Labels
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Урок 184. 00:12:33Preparing The Images
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Урок 185. 00:12:12Turning Data Labels Into Numbers
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Урок 186. 00:09:19Creating Our Own Validation Set
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Урок 187. 00:10:26Preprocess Images
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Урок 188. 00:11:01Preprocess Images 2
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Урок 189. 00:09:38Turning Data Into Batches
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Урок 190. 00:17:55Turning Data Into Batches 2
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Урок 191. 00:12:42Visualizing Our Data
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Урок 192. 00:06:38Preparing Our Inputs and Outputs
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Урок 193. 00:11:43Building A Deep Learning Model
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Урок 194. 00:10:54Building A Deep Learning Model 2
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Урок 195. 00:09:06Building A Deep Learning Model 3
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Урок 196. 00:09:13Building A Deep Learning Model 4
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Урок 197. 00:04:53Summarizing Our Model
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Урок 198. 00:09:27Evaluating Our Model
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Урок 199. 00:04:21Preventing Overfitting
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Урок 200. 00:19:10Training Your Deep Neural Network
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Урок 201. 00:07:31Evaluating Performance With TensorBoard
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Урок 202. 00:15:05Make And Transform Predictons
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Урок 203. 00:15:20Transform Predictions To Text
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Урок 204. 00:14:47Visualizing Model Predictions
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Урок 205. 00:15:53Visualizing And Evaluate Model Predictions 2
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Урок 206. 00:10:40Visualizing And Evaluate Model Predictions 3
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Урок 207. 00:13:35Saving And Loading A Trained Model
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Урок 208. 00:15:03Training Model On Full Dataset
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Урок 209. 00:16:55Making Predictions On Test Images
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Урок 210. 00:14:15Submitting Model to Kaggle
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Урок 211. 00:15:16Making Predictions On Our Images
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Урок 212. 00:02:20Section Overview
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Урок 213. 00:15:04What If I Don't Have Enough Experience?
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Урок 214. 00:02:00JTS: Learn to Learn
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Урок 215. 00:02:44JTS: Start With Why
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Урок 216. 00:17:41CWD: Git + Github
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Урок 217. 00:16:53CWD: Git + Github 2
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Урок 218. 00:14:45Contributing To Open Source
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Урок 219. 00:09:43Contributing To Open Source 2
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Урок 220. 00:06:25What Is A Programming Language
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Урок 221. 00:07:05Python Interpreter
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Урок 222. 00:04:54How To Run Python Code
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Урок 223. 00:07:44Our First Python Program
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Урок 224. 00:06:41Python 2 vs Python 3
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Урок 225. 00:02:10Exercise: How Does Python Work?
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Урок 226. 00:02:06Learning Python
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Урок 227. 00:04:47Python Data Types
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Урок 228. 00:11:10Numbers
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Урок 229. 00:04:30Math Functions
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Урок 230. 00:04:08DEVELOPER FUNDAMENTALS: I
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Урок 231. 00:03:11Operator Precedence
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Урок 232. 00:04:03Optional: bin() and complex
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Урок 233. 00:13:13Variables
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Урок 234. 00:01:37Expressions vs Statements
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Урок 235. 00:02:50Augmented Assignment Operator
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Урок 236. 00:05:30Strings
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Урок 237. 00:01:17String Concatenation
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Урок 238. 00:03:04Type Conversion
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Урок 239. 00:04:24Escape Sequences
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Урок 240. 00:08:24Formatted Strings
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Урок 241. 00:08:58String Indexes
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Урок 242. 00:03:14Immutability
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Урок 243. 00:10:04Built-In Functions + Methods
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Урок 244. 00:03:22Booleans
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Урок 245. 00:08:23Exercise: Type Conversion
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Урок 246. 00:04:43DEVELOPER FUNDAMENTALS: II
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Урок 247. 00:07:22Exercise: Password Checker
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Урок 248. 00:05:02Lists
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Урок 249. 00:07:49List Slicing
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Урок 250. 00:04:12Matrix
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Урок 251. 00:10:29List Methods
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Урок 252. 00:04:25List Methods 2
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Урок 253. 00:04:53List Methods 3
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Урок 254. 00:05:58Common List Patterns
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Урок 255. 00:02:41List Unpacking
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Урок 256. 00:01:52None
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Урок 257. 00:06:21Dictionaries
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Урок 258. 00:02:41DEVELOPER FUNDAMENTALS: III
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Урок 259. 00:03:38Dictionary Keys
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Урок 260. 00:04:38Dictionary Methods
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Урок 261. 00:07:05Dictionary Methods 2
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Урок 262. 00:04:47Tuples
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Урок 263. 00:03:15Tuples 2
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Урок 264. 00:07:25Sets
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Урок 265. 00:08:46Sets 2
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Урок 266. 00:02:35Breaking The Flow
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Урок 267. 00:13:18Conditional Logic
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Урок 268. 00:04:39Indentation In Python
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Урок 269. 00:05:18Truthy vs Falsey
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Урок 270. 00:04:15Ternary Operator
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Урок 271. 00:04:03Short Circuiting
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Урок 272. 00:06:57Logical Operators
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Урок 273. 00:07:48Exercise: Logical Operators
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Урок 274. 00:07:37is vs ==
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Урок 275. 00:07:02For Loops
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Урок 276. 00:06:44Iterables
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Урок 277. 00:03:24Exercise: Tricky Counter
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Урок 278. 00:05:39range()
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Урок 279. 00:04:38enumerate()
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Урок 280. 00:06:29While Loops
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Урок 281. 00:05:50While Loops 2
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Урок 282. 00:04:16break, continue, pass
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Урок 283. 00:08:49Our First GUI
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Урок 284. 00:06:35DEVELOPER FUNDAMENTALS: IV
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Урок 285. 00:03:55Exercise: Find Duplicates
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Урок 286. 00:07:42Functions
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Урок 287. 00:04:25Parameters and Arguments
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Урок 288. 00:05:41Default Parameters and Keyword Arguments
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Урок 289. 00:13:12return
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Урок 290. 00:04:34Methods vs Functions
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Урок 291. 00:03:48Docstrings
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Урок 292. 00:04:39Clean Code
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Урок 293. 00:07:57*args and **kwargs
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Урок 294. 00:04:19Exercise: Functions
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Урок 295. 00:03:38Scope
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Урок 296. 00:06:56Scope Rules
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Урок 297. 00:06:14global Keyword
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Урок 298. 00:03:22nonlocal Keyword
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Урок 299. 00:03:39Why Do We Need Scope?
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Урок 300. 00:09:24Pure Functions
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Урок 301. 00:06:31map()
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Урок 302. 00:04:24filter()
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Урок 303. 00:03:29zip()
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Урок 304. 00:07:32reduce()
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Урок 305. 00:08:38List Comprehensions
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Урок 306. 00:06:27Set Comprehensions
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Урок 307. 00:04:37Exercise: Comprehensions
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Урок 308. 00:10:55Modules in Python
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Урок 309. 00:08:20Optional: PyCharm
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Урок 310. 00:10:46Packages in Python
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Урок 311. 00:07:04Different Ways To Import
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Урок 312. 00:02:45Thank You
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