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Премиум
  1. Урок 1. 00:03:34
    Introduction to the Course
  2. Урок 2. 00:00:37
    Course Help and Welcome
  3. Урок 3. 00:11:15
    Python Environment Setup
  4. Урок 4. 00:13:49
    Jupyter Notebooks
  5. Урок 5. 00:09:52
    Optional: Virtual Environments
  6. Урок 6. 00:00:18
    Welcome to the Python Crash Course Section!
  7. Урок 7. 00:01:27
    Introduction to Python Crash Course
  8. Урок 8. 00:19:31
    Python Crash Course - Part 1
  9. Урок 9. 00:15:15
    Python Crash Course - Part 2
  10. Урок 10. 00:16:40
    Python Crash Course - Part 3
  11. Урок 11. 00:15:38
    Python Crash Course - Part 4
  12. Урок 12. 00:03:36
    Python Crash Course Exercises - Overview
  13. Урок 13. 00:11:57
    Python Crash Course Exercises - Solutions
  14. Урок 14. 00:00:12
    Welcome to the NumPy Section!
  15. Урок 15. 00:02:14
    Introduction to Numpy
  16. Урок 16. 00:16:51
    Numpy Arrays
  17. Урок 17. 00:18:24
    Numpy Array Indexing
  18. Урок 18. 00:07:05
    Numpy Operations
  19. Урок 19. 00:02:47
    Numpy Exercises Overview
  20. Урок 20. 00:15:33
    Numpy Exercises Solutions
  21. Урок 21. 00:00:15
    Welcome to the Pandas Section!
  22. Урок 22. 00:01:45
    Introduction to Pandas
  23. Урок 23. 00:10:40
    Series
  24. Урок 24. 00:15:32
    DataFrames - Part 1
  25. Урок 25. 00:17:11
    DataFrames - Part 2
  26. Урок 26. 00:09:13
    DataFrames - Part 3
  27. Урок 27. 00:06:20
    Missing Data
  28. Урок 28. 00:06:50
    Groupby
  29. Урок 29. 00:08:57
    Merging Joining and Concatenating
  30. Урок 30. 00:12:05
    Operations
  31. Урок 31. 00:14:01
    Data Input and Output
  32. Урок 32. 00:01:56
    SF Salaries Exercise Overview
  33. Урок 33. 00:15:27
    SF Salaries Solutions
  34. Урок 34. 00:02:12
    Ecommerce Purchases Exercise Overview
  35. Урок 35. 00:15:14
    Ecommerce Purchases Exercise Solutions
  36. Урок 36. 00:00:23
    Welcome to the Data Visualization Section!
  37. Урок 37. 00:03:03
    Introduction to Matplotlib
  38. Урок 38. 00:16:59
    Matplotlib Part 1
  39. Урок 39. 00:15:52
    Matplotlib Part 2
  40. Урок 40. 00:11:53
    Matplotlib Part 3
  41. Урок 41. 00:01:48
    Matplotlib Exercises Overview
  42. Урок 42. 00:10:20
    Matplotlib Exercises - Solutions
  43. Урок 43. 00:02:59
    Introduction to Seaborn
  44. Урок 44. 00:18:22
    Distribution Plots
  45. Урок 45. 00:17:19
    Categorical Plots
  46. Урок 46. 00:10:15
    Matrix Plots
  47. Урок 47. 00:08:31
    Grids
  48. Урок 48. 00:07:15
    Regression Plots
  49. Урок 49. 00:08:22
    Style and Color
  50. Урок 50. 00:01:54
    Seaborn Exercise Overview
  51. Урок 51. 00:07:09
    Seaborn Exercise Solutions
  52. Урок 52. 00:13:28
    Pandas Built-in Data Visualization
  53. Урок 53. 00:01:24
    Pandas Data Visualization Exercise
  54. Урок 54. 00:08:56
    Pandas Data Visualization Exercise- Solutions
  55. Урок 55. 00:03:23
    Introduction to Plotly and Cufflinks
  56. Урок 56. 00:18:39
    Plotly and Cufflinks
  57. Урок 57. 00:00:59
    Introduction to Geographical Plotting
  58. Урок 58. 00:19:27
    Choropleth Maps - Part 1 - USA
  59. Урок 59. 00:06:54
    Choropleth Maps - Part 2 - World
  60. Урок 60. 00:03:13
    Choropleth Exercises
  61. Урок 61. 00:10:02
    Choropleth Exercises - Solutions
  62. Урок 62. 00:00:18
    Welcome to the Data Capstone Projects!
  63. Урок 63. 00:02:08
    911 Calls Project Overview
  64. Урок 64. 00:14:30
    911 Calls Solutions - Part 1
  65. Урок 65. 00:17:38
    911 Calls Solutions - Part 2
  66. Урок 66. 00:03:07
    Finance Data Project Overview
  67. Урок 67. 00:16:14
    Finance Project - Solutions Part 1
  68. Урок 68. 00:18:12
    Finance Project - Solutions Part 2
  69. Урок 69. 00:06:25
    Finance Project - Solutions Part 3
  70. Урок 70. 00:00:32
    Welcome to the Machine Learning Section!
  71. Урок 71. 00:08:22
    Supervised Learning Overview
  72. Урок 72. 00:16:38
    Evaluating Performance - Classification Error Metrics
  73. Урок 73. 00:05:37
    Evaluating Performance - Regression Error Metrics
  74. Урок 74. 00:09:28
    Machine Learning with Python
  75. Урок 75. 00:04:34
    Linear Regression Theory
  76. Урок 76. 00:18:17
    Linear Regression with Python - Part 1
  77. Урок 77. 00:07:06
    Linear Regression with Python - Part 2
  78. Урок 78. 00:02:32
    Linear Regression Project Overview
  79. Урок 79. 00:18:44
    Linear Regression Project Solution
  80. Урок 80. 00:06:26
    Bias Variance Trade-Off
  81. Урок 81. 00:11:54
    Logistic Regression Theory
  82. Урок 82. 00:17:44
    Logistic Regression with Python - Part 1
  83. Урок 83. 00:16:58
    Logistic Regression with Python - Part 2
  84. Урок 84. 00:08:16
    Logistic Regression with Python - Part 3
  85. Урок 85. 00:01:37
    Logistic Regression Project Overview
  86. Урок 86. 00:11:06
    Logistic Regression Project Solutions
  87. Урок 87. 00:05:40
    KNN Theory
  88. Урок 88. 00:19:40
    KNN with Python
  89. Урок 89. 00:01:13
    KNN Project Overview
  90. Урок 90. 00:14:15
    KNN Project Solutions
  91. Урок 91. 00:06:54
    Introduction to Tree Methods
  92. Урок 92. 00:13:58
    Decision Trees and Random Forest with Python
  93. Урок 93. 00:03:11
    Decision Trees and Random Forest Project Overview
  94. Урок 94. 00:12:15
    Decision Trees and Random Forest Solutions Part 1
  95. Урок 95. 00:08:47
    Decision Trees and Random Forest Solutions Part 2
  96. Урок 96. 00:04:37
    SVM Theory
  97. Урок 97. 00:17:53
    Support Vector Machines with Python
  98. Урок 98. 00:02:22
    SVM Project Overview
  99. Урок 99. 00:10:10
    SVM Project Solutions
  100. Урок 100. 00:05:16
    K Means Algorithm Theory
  101. Урок 101. 00:12:36
    K Means with Python
  102. Урок 102. 00:02:54
    K Means Project Overview
  103. Урок 103. 00:16:39
    K Means Project Solutions
  104. Урок 104. 00:03:27
    Principal Component Analysis
  105. Урок 105. 00:17:00
    PCA with Python
  106. Урок 106. 00:04:14
    Recommender Systems
  107. Урок 107. 00:13:38
    Recommender Systems with Python - Part 1
  108. Урок 108. 00:13:22
    Recommender Systems with Python - Part 2
  109. Урок 109. 00:05:08
    Natural Language Processing Theory
  110. Урок 110. 00:16:03
    NLP with Python - Part 1
  111. Урок 111. 00:18:48
    NLP with Python - Part 2
  112. Урок 112. 00:17:31
    NLP with Python - Part 3
  113. Урок 113. 00:02:05
    NLP Project Overview
  114. Урок 114. 00:19:27
    NLP Project Solutions
  115. Урок 115. 00:00:22
    Welcome to the Deep Learning Section!
  116. Урок 116. 00:02:16
    Introduction to Artificial Neural Networks (ANN)
  117. Урок 117. 00:10:40
    Perceptron Model
  118. Урок 118. 00:07:20
    Neural Networks
  119. Урок 119. 00:10:40
    Activation Functions
  120. Урок 120. 00:10:35
    Multi-Class Classification Considerations
  121. Урок 121. 00:18:14
    Cost Functions and Gradient Descent
  122. Урок 122. 00:14:48
    Backpropagation
  123. Урок 123. 00:02:14
    TensorFlow vs Keras
  124. Урок 124. 00:10:50
    TF Syntax Basics - Part One - Preparing the Data
  125. Урок 125. 00:14:00
    TF Syntax Basics - Part Two - Creating and Training the Model
  126. Урок 126. 00:12:57
    TF Syntax Basics - Part Three - Model Evaluation
  127. Урок 127. 00:18:51
    TF Regression Code Along - Exploratory Data Analysis
  128. Урок 128. 00:13:16
    TF Regression Code Along - Exploratory Data Analysis - Continued
  129. Урок 129. 00:08:43
    TF Regression Code Along - Data Preprocessing and Creating a Model
  130. Урок 130. 00:11:24
    TF Regression Code Along - Model Evaluation and Predictions
  131. Урок 131. 00:08:06
    TF Classification Code Along - EDA and Preprocessing
  132. Урок 132. 00:16:51
    TF Classification - Dealing with Overfitting and Evaluation
  133. Урок 133. 00:01:41
    TensorFlow 2.0 Project Options Overview
  134. Урок 134. 00:07:42
    TensorFlow 2.0 Project Notebook Overview
  135. Урок 135. 00:20:36
    Keras Project Solutions - Dealing with Missing Data
  136. Урок 136. 00:14:47
    Keras Project Solutions - Dealing with Missing Data - Part Two
  137. Урок 137. 00:12:03
    Keras Project Solutions - Categorical Data
  138. Урок 138. 00:17:24
    Keras Project Solutions - Data PreProcessing
  139. Урок 139. 00:03:46
    Keras Project Solutions - Data PreProcessing
  140. Урок 140. 00:03:58
    Keras Project Solutions - Creating and Training a Model
  141. Урок 141. 00:09:43
    Keras Project Solutions - Model Evaluation
  142. Урок 142. 00:18:23
    Tensorboard
  143. Урок 143. 00:00:24
    Welcome to the Big Data Section!
  144. Урок 144. 00:05:32
    Big Data Overview
  145. Урок 145. 00:09:01
    Spark Overview
  146. Урок 146. 00:04:14
    AWS Account Set-Up
  147. Урок 147. 00:16:19
    EC2 Instance Set-Up
  148. Урок 148. 00:04:50
    SSH with Mac or Linux
  149. Урок 149. 00:23:49
    PySpark Setup
  150. Урок 150. 00:05:27
    Lambda Expressions Review
  151. Урок 151. 00:08:18
    Introduction to Spark and Python
  152. Урок 152. 00:23:10
    RDD Transformations and Actions