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[Udemy] Practical AI with Python and Reinforcement Learning ()

  • 收录时间:2022-03-22 05:35:10
  • 文件大小:7GB
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  • 最近下载:2022-03-22 05:35:10
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文件列表

  1. 11 Classical Q Learning/019 Q-Learning Exercise Project - Solutions.mp4 177MB
  2. 10 Open AI Gym Overview/003 OpenAI Gym - Documentation Tour.mp4 147MB
  3. 07 Artificial Neural Network and TensorFlow Basics/027 Tensorboard.mp4 144MB
  4. 07 Artificial Neural Network and TensorFlow Basics/020 Keras Project Solution - Exploratoy Data Analysis.mp4 144MB
  5. 10 Open AI Gym Overview/005 OpenAI Gym - Working with the Environment.mp4 138MB
  6. 07 Artificial Neural Network and TensorFlow Basics/012 Keras Regression - Exploratory Data Analysis.mp4 137MB
  7. 07 Artificial Neural Network and TensorFlow Basics/023 Keras Project Solutions - Categorical Data.mp4 125MB
  8. 04 Matplotlib and Visualization Overview/011 Matplotlib Exercise Questions - Solutions.mp4 123MB
  9. 10 Open AI Gym Overview/006 OpenAI Gym - Agent Interacting with the Environment.mp4 116MB
  10. 06 Pandas and Scikit-Learn Crash Course/004 Pandas - DataFrames - Part One.mp4 114MB
  11. 07 Artificial Neural Network and TensorFlow Basics/017 Keras Classification - Overfitting and Evaluation.mp4 111MB
  12. 03 Numpy Basics Overview/002 NumPy Arrays.mp4 110MB
  13. 11 Classical Q Learning/017 Continuous Q-Learning - Part Six - Training and Usage.mp4 109MB
  14. 11 Classical Q Learning/010 Q-Learning Implementation - Part Four - Agent Training.mp4 107MB
  15. 12 Deep Q-Learning/011 DQN Manual Implementation - Part Four - Model Training.mp4 107MB
  16. 08 Convolutional Neural Networks with TensorFlow/007 CNN on MNIST - Creating and Training the Model.mp4 99MB
  17. 02 Course Set-Up and Installation Procedures/001 Anaconda and Jupyter Notebook Install and Setup.mp4 99MB
  18. 07 Artificial Neural Network and TensorFlow Basics/021 Keras Project Solutions - Missing Data - Part One.mp4 97MB
  19. 06 Pandas and Scikit-Learn Crash Course/007 Pandas - DataFrames - Part Four.mp4 97MB
  20. 04 Matplotlib and Visualization Overview/006 Matplotlib - Subplots Functionality.mp4 96MB
  21. 12 Deep Q-Learning/006 DQN Theory and Intuition - Part Four - Experience Replay.mp4 96MB
  22. 11 Classical Q Learning/009 Q-Learning Implementation - Part Three - Update Functions.mp4 93MB
  23. 08 Convolutional Neural Networks with TensorFlow/014 CNN on Real Image Files - Creating the Model.mp4 90MB
  24. 06 Pandas and Scikit-Learn Crash Course/006 Pandas - DataFrames - Part Three.mp4 90MB
  25. 12 Deep Q-Learning/005 DQN Theory and Intuition - Part Three - Feedback and Function Approximation.mp4 88MB
  26. 11 Classical Q Learning/007 Q-Learning Implementation - Part One - Environment Setup.mp4 88MB
  27. 08 Convolutional Neural Networks with TensorFlow/013 CNN on Real Image Files - Data Generation.mp4 88MB
  28. 11 Classical Q Learning/015 Continuous Q-Learning - Part Four - Discretization Implementation.mp4 86MB
  29. 11 Classical Q Learning/013 Continuous Q-Learning Theory - Part Two- Q-Table Shape.mp4 86MB
  30. 07 Artificial Neural Network and TensorFlow Basics/022 Keras Project Solutions - Dealing with Missing Data - Part Two.mp4 85MB
  31. 12 Deep Q-Learning/010 DQN Manual Implementation - Part Three - Hyperparameters and Functions.mp4 85MB
  32. 07 Artificial Neural Network and TensorFlow Basics/010 Keras Syntax - Creating and Training the Model.mp4 84MB
  33. 12 Deep Q-Learning/015 DQN - Keras-RL2 - Part Four - DQN Agent.mp4 84MB
  34. 12 Deep Q-Learning/007 DQN Theory and Intuition - Part Five - Mapping Key Ideas to Code.mp4 81MB
  35. 04 Matplotlib and Visualization Overview/008 Matplotlib Styling - Colors and Styles.mp4 81MB
  36. 07 Artificial Neural Network and TensorFlow Basics/019 Keras Project Notebook Exercise Overview.mp4 81MB
  37. 08 Convolutional Neural Networks with TensorFlow/012 CNN on Real Image Files - Reading in the Data.mp4 80MB
  38. 11 Classical Q Learning/003 Q-Learning Theory - Part One - Table Intuition.mp4 78MB
  39. 06 Pandas and Scikit-Learn Crash Course/009 Scikit-Learn - Using Metrics.mp4 77MB
  40. 07 Artificial Neural Network and TensorFlow Basics/013 Keras Regression - EDA Continued.mp4 76MB
  41. 07 Artificial Neural Network and TensorFlow Basics/006 Cost Functions and Gradient Descent.mp4 76MB
  42. 08 Convolutional Neural Networks with TensorFlow/002 Image Filters and Kernels.mp4 72MB
  43. 05 Machine Learning, Deep Learning, and Reinforcement Learning/002 Supervised Machine Learning Process.mp4 72MB
  44. 02 Course Set-Up and Installation Procedures/003 Environment Setup Walkthrough.mp4 71MB
  45. 10 Open AI Gym Overview/002 OpenAI Overview and History.mp4 70MB
  46. 07 Artificial Neural Network and TensorFlow Basics/015 Keras Regression - Model Evaluation and Predictions.mp4 69MB
  47. 11 Classical Q Learning/018 Q-Learning Exercise Project.mp4 66MB
  48. 07 Artificial Neural Network and TensorFlow Basics/011 Keras Syntax - Model Evaluation.mp4 65MB
  49. 08 Convolutional Neural Networks with TensorFlow/009 CNN on CIFAR-10 - The Data.mp4 64MB
  50. 07 Artificial Neural Network and TensorFlow Basics/026 Keras Project Solutions - Model Evaluation.mp4 63MB
  51. 12 Deep Q-Learning/017 DQN - Exercise Solutions.mp4 63MB
  52. 07 Artificial Neural Network and TensorFlow Basics/004 Activation Functions.mp4 63MB
  53. 09 Reinforcement Learning - Core Concepts/002 Agents, Environments, and Policy.mp4 62MB
  54. 06 Pandas and Scikit-Learn Crash Course/008 Scikit-Learn - Using Train-Test-Split.mp4 60MB
  55. 08 Convolutional Neural Networks with TensorFlow/006 CNN on MNIST - The Data.mp4 60MB
  56. 04 Matplotlib and Visualization Overview/004 Matplotlib - Implementing Figures and Axes.mp4 59MB
  57. 11 Classical Q Learning/006 Q-Learning Theory - Part Four - Programmatic Q Updates.mp4 58MB
  58. 08 Convolutional Neural Networks with TensorFlow/003 Convolutional Layers.mp4 58MB
  59. 07 Artificial Neural Network and TensorFlow Basics/007 Backpropagation.mp4 58MB
  60. 09 Reinforcement Learning - Core Concepts/003 Rewards, Discount Factors, and Bellman Equation.mp4 57MB
  61. 11 Classical Q Learning/011 Q-Learning Implementation - Part Five - Visualization and Utilization.mp4 57MB
  62. 07 Artificial Neural Network and TensorFlow Basics/016 Keras Classification - EDA and Preprocessing.mp4 56MB
  63. 08 Convolutional Neural Networks with TensorFlow/017 CNN Exercise Project Solutions.mp4 56MB
  64. 01 Course Overview/002 COURSE_NOTEBOOKS.zip 55MB
  65. 02 Course Set-Up and Installation Procedures/004 COURSE_NOTEBOOKS.zip 55MB
  66. 05 Machine Learning, Deep Learning, and Reinforcement Learning/001 What is Machine Learning, Deep Learning, and Artificial Intelligence_.mp4 55MB
  67. 11 Classical Q Learning/012 Continuous Q-Learning Theory - Part One - Environment Setup.mp4 54MB
  68. 11 Classical Q Learning/004 Q-Learning Theory - Part Two - Q Target Equation.mp4 54MB
  69. 06 Pandas and Scikit-Learn Crash Course/005 Pandas - DataFrames - Part Two.mp4 54MB
  70. 12 Deep Q-Learning/012 DQN - Keras-RL2 - Part One - Overview.mp4 54MB
  71. 04 Matplotlib and Visualization Overview/002 Matplotlib Basics.mp4 54MB
  72. 04 Matplotlib and Visualization Overview/010 Matplotlib Exercise Questions Overview.mp4 51MB
  73. 07 Artificial Neural Network and TensorFlow Basics/009 Keras Syntax - Preparing the Data.mp4 50MB
  74. 03 Numpy Basics Overview/004 Numpy Operations - Part Two.mp4 49MB
  75. 03 Numpy Basics Overview/006 Numpy Exercise Solutions.mp4 49MB
  76. 07 Artificial Neural Network and TensorFlow Basics/002 Perceptron Model.mp4 48MB
  77. 07 Artificial Neural Network and TensorFlow Basics/014 Keras Regression - Data Preprocessing and Model Creation.mp4 47MB
  78. 08 Convolutional Neural Networks with TensorFlow/015 CNN on Real Image Files - Model Evaluation.mp4 47MB
  79. 12 Deep Q-Learning/004 DQN Theory and Intuition - Part Two - Neural Networks for RL.mp4 47MB
  80. 03 Numpy Basics Overview/003 Numpy Operations - Part One.mp4 46MB
  81. 07 Artificial Neural Network and TensorFlow Basics/005 Multi-Class Classification Considerations.mp4 46MB
  82. 06 Pandas and Scikit-Learn Crash Course/003 Pandas - Series Part Two.mp4 45MB
  83. 11 Classical Q Learning/016 Continuous Q-Learning - Part Five - Functions and Hyperparameters.mp4 45MB
  84. 08 Convolutional Neural Networks with TensorFlow/010 CNN on CIFAR-10 - Evaluating the Model.mp4 45MB
  85. 01 Course Overview/002 Course Curriculum Overview.mp4 44MB
  86. 11 Classical Q Learning/008 Q-Learning Implementation - Part Two - Table and Hyperparameters.mp4 43MB
  87. 01 Course Overview/003 Course Success and Overview.mp4 42MB
  88. 04 Matplotlib and Visualization Overview/009 Advanced Matplotlib Commands (Optional).mp4 40MB
  89. 06 Pandas and Scikit-Learn Crash Course/002 Pandas - Series Part One.mp4 39MB
  90. 08 Convolutional Neural Networks with TensorFlow/008 CNN on MNIST - Model Evaluation.mp4 38MB
  91. 11 Classical Q Learning/005 Q-Learning Theory - Part Three - Q-Update Equation.mp4 38MB
  92. 10 Open AI Gym Overview/004 OpenAI Gym - Environment Key Ideas.mp4 37MB
  93. 07 Artificial Neural Network and TensorFlow Basics/003 Neural Networks.mp4 36MB
  94. 04 Matplotlib and Visualization Overview/007 Matplotlib Styling - Legends.mp4 34MB
  95. 12 Deep Q-Learning/009 DQN Manual Implementation - Part Two - Artificial Neural Network.mp4 32MB
  96. 07 Artificial Neural Network and TensorFlow Basics/025 Keras Project Solutions- Creating and Training the Model.mp4 30MB
  97. 12 Deep Q-Learning/002 History of DQN.mp4 29MB
  98. 12 Deep Q-Learning/016 DQN - Exercise Overview.mp4 28MB
  99. 08 Convolutional Neural Networks with TensorFlow/011 Downloading Data Set for Real Image Lectures.mp4 28MB
  100. 08 Convolutional Neural Networks with TensorFlow/004 Pooling Layers.mp4 28MB
  101. 09 Reinforcement Learning - Core Concepts/004 Deterministic vs. Stochastic Processes.mp4 27MB
  102. 11 Classical Q Learning/002 History of Q-Learning.mp4 27MB
  103. 12 Deep Q-Learning/014 DQN - Keras-RL2 - Part Three - Creating the ANN.mp4 26MB
  104. 04 Matplotlib and Visualization Overview/003 Matplotlib - Understanding the Figure Object.mp4 26MB
  105. 08 Convolutional Neural Networks with TensorFlow/005 MNIST Data Set Overview.mp4 25MB
  106. 11 Classical Q Learning/014 Continuous Q-Learning Theory - Part Three - Discretization Theory.mp4 25MB
  107. 07 Artificial Neural Network and TensorFlow Basics/024 Keras Project Solutions - Data Preprocessing.mp4 24MB
  108. 12 Deep Q-Learning/003 DQN Theory and Intuition - Part One - Review of Core RL Ideas.mp4 24MB
  109. 04 Matplotlib and Visualization Overview/005 Matplotlib - Figure Parameters.mp4 24MB
  110. 11 Classical Q Learning/001 Introduction to Classical Q-Learning Overview.mp4 23MB
  111. 04 Matplotlib and Visualization Overview/001 Introduction to Matplotlib.mp4 22MB
  112. 12 Deep Q-Learning/008 DQN Manual Implementation - Part One - Imports and Environment.mp4 21MB
  113. 08 Convolutional Neural Networks with TensorFlow/016 CNN Exercise Project Overview.mp4 18MB
  114. 12 Deep Q-Learning/013 DQN - Keras-RL2 - Part Two - Imports and Environment.mp4 14MB
  115. 03 Numpy Basics Overview/005 Numpy Exercise Overview.mp4 12MB
  116. 03 Numpy Basics Overview/001 Introduction to Numpy Section.mp4 11MB
  117. 09 Reinforcement Learning - Core Concepts/001 Overview of Core Concepts for Reinforcement Learning Section.mp4 11MB
  118. 07 Artificial Neural Network and TensorFlow Basics/008 TensorFlow vs. Keras Explained.mp4 10MB
  119. 12 Deep Q-Learning/001 DQN Section Overview.mp4 10MB
  120. 07 Artificial Neural Network and TensorFlow Basics/001 Introduction to Artificial Neural Networks.mp4 10MB
  121. 07 Artificial Neural Network and TensorFlow Basics/018 Keras Classification - Overview of Project Options.mp4 8MB
  122. 08 Convolutional Neural Networks with TensorFlow/001 Convolutional Neural Networks Section Overview.mp4 8MB
  123. 10 Open AI Gym Overview/001 Introduction to OpenAI Gym Section.mp4 6MB
  124. 12 Deep Q-Learning/110 DQNNaturePaper.pdf 4MB
  125. 10 Open AI Gym Overview/005 OpenAI Gym - Working with the Environment.en.srt 43KB
  126. 11 Classical Q Learning/019 Q-Learning Exercise Project - Solutions.en.srt 34KB
  127. 03 Numpy Basics Overview/002 NumPy Arrays.en.srt 33KB
  128. 10 Open AI Gym Overview/006 OpenAI Gym - Agent Interacting with the Environment.en.srt 32KB
  129. 11 Classical Q Learning/017 Continuous Q-Learning - Part Six - Training and Usage.en.srt 32KB
  130. 12 Deep Q-Learning/005 DQN Theory and Intuition - Part Three - Feedback and Function Approximation.en.srt 31KB
  131. 07 Artificial Neural Network and TensorFlow Basics/027 Tensorboard.en.srt 31KB
  132. 06 Pandas and Scikit-Learn Crash Course/004 Pandas - DataFrames - Part One.en.srt 30KB
  133. 07 Artificial Neural Network and TensorFlow Basics/020 Keras Project Solution - Exploratoy Data Analysis.en.srt 30KB
  134. 12 Deep Q-Learning/006 DQN Theory and Intuition - Part Four - Experience Replay.en.srt 30KB
  135. 04 Matplotlib and Visualization Overview/006 Matplotlib - Subplots Functionality.en.srt 30KB
  136. 07 Artificial Neural Network and TensorFlow Basics/006 Cost Functions and Gradient Descent.en.srt 29KB
  137. 07 Artificial Neural Network and TensorFlow Basics/012 Keras Regression - Exploratory Data Analysis.en.srt 28KB
  138. 12 Deep Q-Learning/010 DQN Manual Implementation - Part Three - Hyperparameters and Functions.en.srt 28KB
  139. 07 Artificial Neural Network and TensorFlow Basics/023 Keras Project Solutions - Categorical Data.en.srt 27KB
  140. 11 Classical Q Learning/015 Continuous Q-Learning - Part Four - Discretization Implementation.en.srt 27KB
  141. 11 Classical Q Learning/010 Q-Learning Implementation - Part Four - Agent Training.en.srt 27KB
  142. 08 Convolutional Neural Networks with TensorFlow/007 CNN on MNIST - Creating and Training the Model.en.srt 26KB
  143. 12 Deep Q-Learning/011 DQN Manual Implementation - Part Four - Model Training.en.srt 26KB
  144. 04 Matplotlib and Visualization Overview/011 Matplotlib Exercise Questions - Solutions.en.srt 26KB
  145. 11 Classical Q Learning/009 Q-Learning Implementation - Part Three - Update Functions.en.srt 26KB
  146. 11 Classical Q Learning/013 Continuous Q-Learning Theory - Part Two- Q-Table Shape.en.srt 26KB
  147. 07 Artificial Neural Network and TensorFlow Basics/017 Keras Classification - Overfitting and Evaluation.en.srt 25KB
  148. 08 Convolutional Neural Networks with TensorFlow/013 CNN on Real Image Files - Data Generation.en.srt 24KB
  149. 11 Classical Q Learning/007 Q-Learning Implementation - Part One - Environment Setup.en.srt 24KB
  150. 12 Deep Q-Learning/007 DQN Theory and Intuition - Part Five - Mapping Key Ideas to Code.en.srt 24KB
  151. 11 Classical Q Learning/003 Q-Learning Theory - Part One - Table Intuition.en.srt 23KB
  152. 10 Open AI Gym Overview/003 OpenAI Gym - Documentation Tour.en.srt 23KB
  153. 12 Deep Q-Learning/015 DQN - Keras-RL2 - Part Four - DQN Agent.en.srt 23KB
  154. 06 Pandas and Scikit-Learn Crash Course/009 Scikit-Learn - Using Metrics.en.srt 22KB
  155. 02 Course Set-Up and Installation Procedures/001 Anaconda and Jupyter Notebook Install and Setup.en.srt 22KB
  156. 08 Convolutional Neural Networks with TensorFlow/003 Convolutional Layers.en.srt 22KB
  157. 06 Pandas and Scikit-Learn Crash Course/007 Pandas - DataFrames - Part Four.en.srt 22KB
  158. 04 Matplotlib and Visualization Overview/008 Matplotlib Styling - Colors and Styles.en.srt 22KB
  159. 07 Artificial Neural Network and TensorFlow Basics/007 Backpropagation.en.srt 22KB
  160. 07 Artificial Neural Network and TensorFlow Basics/021 Keras Project Solutions - Missing Data - Part One.en.srt 22KB
  161. 04 Matplotlib and Visualization Overview/004 Matplotlib - Implementing Figures and Axes.en.srt 22KB
  162. 08 Convolutional Neural Networks with TensorFlow/012 CNN on Real Image Files - Reading in the Data.en.srt 22KB
  163. 07 Artificial Neural Network and TensorFlow Basics/010 Keras Syntax - Creating and Training the Model.en.srt 21KB
  164. 06 Pandas and Scikit-Learn Crash Course/006 Pandas - DataFrames - Part Three.en.srt 21KB
  165. 08 Convolutional Neural Networks with TensorFlow/014 CNN on Real Image Files - Creating the Model.en.srt 21KB
  166. 11 Classical Q Learning/012 Continuous Q-Learning Theory - Part One - Environment Setup.en.srt 21KB
  167. 05 Machine Learning, Deep Learning, and Reinforcement Learning/002 Supervised Machine Learning Process.en.srt 20KB
  168. 04 Matplotlib and Visualization Overview/002 Matplotlib Basics.en.srt 20KB
  169. 09 Reinforcement Learning - Core Concepts/003 Rewards, Discount Factors, and Bellman Equation.en.srt 20KB
  170. 07 Artificial Neural Network and TensorFlow Basics/013 Keras Regression - EDA Continued.en.srt 20KB
  171. 08 Convolutional Neural Networks with TensorFlow/006 CNN on MNIST - The Data.en.srt 19KB
  172. 09 Reinforcement Learning - Core Concepts/002 Agents, Environments, and Policy.en.srt 19KB
  173. 07 Artificial Neural Network and TensorFlow Basics/022 Keras Project Solutions - Dealing with Missing Data - Part Two.en.srt 19KB
  174. 08 Convolutional Neural Networks with TensorFlow/002 Image Filters and Kernels.en.srt 19KB
  175. 07 Artificial Neural Network and TensorFlow Basics/011 Keras Syntax - Model Evaluation.en.srt 19KB
  176. 08 Convolutional Neural Networks with TensorFlow/009 CNN on CIFAR-10 - The Data.en.srt 18KB
  177. 06 Pandas and Scikit-Learn Crash Course/008 Scikit-Learn - Using Train-Test-Split.en.srt 18KB
  178. 10 Open AI Gym Overview/002 OpenAI Overview and History.en.srt 18KB
  179. 07 Artificial Neural Network and TensorFlow Basics/004 Activation Functions.en.srt 17KB
  180. 02 Course Set-Up and Installation Procedures/003 Environment Setup Walkthrough.en.srt 17KB
  181. 11 Classical Q Learning/008 Q-Learning Implementation - Part Two - Table and Hyperparameters.en.srt 17KB
  182. 12 Deep Q-Learning/004 DQN Theory and Intuition - Part Two - Neural Networks for RL.en.srt 17KB
  183. 05 Machine Learning, Deep Learning, and Reinforcement Learning/001 What is Machine Learning, Deep Learning, and Artificial Intelligence_.en.srt 17KB
  184. 07 Artificial Neural Network and TensorFlow Basics/015 Keras Regression - Model Evaluation and Predictions.en.srt 17KB
  185. 03 Numpy Basics Overview/003 Numpy Operations - Part One.en.srt 17KB
  186. 07 Artificial Neural Network and TensorFlow Basics/005 Multi-Class Classification Considerations.en.srt 17KB
  187. 11 Classical Q Learning/004 Q-Learning Theory - Part Two - Q Target Equation.en.srt 17KB
  188. 11 Classical Q Learning/016 Continuous Q-Learning - Part Five - Functions and Hyperparameters.en.srt 16KB
  189. 07 Artificial Neural Network and TensorFlow Basics/009 Keras Syntax - Preparing the Data.en.srt 16KB
  190. 11 Classical Q Learning/011 Q-Learning Implementation - Part Five - Visualization and Utilization.en.srt 16KB
  191. 07 Artificial Neural Network and TensorFlow Basics/002 Perceptron Model.en.srt 16KB
  192. 06 Pandas and Scikit-Learn Crash Course/003 Pandas - Series Part Two.en.srt 16KB
  193. 01 Course Overview/002 Course Curriculum Overview.en.srt 16KB
  194. 12 Deep Q-Learning/017 DQN - Exercise Solutions.en.srt 15KB
  195. 11 Classical Q Learning/006 Q-Learning Theory - Part Four - Programmatic Q Updates.en.srt 15KB
  196. 07 Artificial Neural Network and TensorFlow Basics/026 Keras Project Solutions - Model Evaluation.en.srt 15KB
  197. 06 Pandas and Scikit-Learn Crash Course/002 Pandas - Series Part One.en.srt 14KB
  198. 06 Pandas and Scikit-Learn Crash Course/005 Pandas - DataFrames - Part Two.en.srt 14KB
  199. 10 Open AI Gym Overview/004 OpenAI Gym - Environment Key Ideas.en.srt 14KB
  200. 07 Artificial Neural Network and TensorFlow Basics/019 Keras Project Notebook Exercise Overview.en.srt 13KB
  201. 08 Convolutional Neural Networks with TensorFlow/015 CNN on Real Image Files - Model Evaluation.en.srt 13KB
  202. 08 Convolutional Neural Networks with TensorFlow/017 CNN Exercise Project Solutions.en.srt 13KB
  203. 07 Artificial Neural Network and TensorFlow Basics/014 Keras Regression - Data Preprocessing and Model Creation.en.srt 13KB
  204. 03 Numpy Basics Overview/004 Numpy Operations - Part Two.en.srt 13KB
  205. 11 Classical Q Learning/018 Q-Learning Exercise Project.en.srt 12KB
  206. 07 Artificial Neural Network and TensorFlow Basics/016 Keras Classification - EDA and Preprocessing.en.srt 12KB
  207. 01 Course Overview/003 Course Success and Overview.en.srt 12KB
  208. 04 Matplotlib and Visualization Overview/003 Matplotlib - Understanding the Figure Object.en.srt 12KB
  209. 12 Deep Q-Learning/012 DQN - Keras-RL2 - Part One - Overview.en.srt 12KB
  210. 11 Classical Q Learning/005 Q-Learning Theory - Part Three - Q-Update Equation.en.srt 12KB
  211. 07 Artificial Neural Network and TensorFlow Basics/003 Neural Networks.en.srt 12KB
  212. 12 Deep Q-Learning/009 DQN Manual Implementation - Part Two - Artificial Neural Network.en.srt 12KB
  213. 08 Convolutional Neural Networks with TensorFlow/010 CNN on CIFAR-10 - Evaluating the Model.en.srt 11KB
  214. 03 Numpy Basics Overview/006 Numpy Exercise Solutions.en.srt 11KB
  215. 08 Convolutional Neural Networks with TensorFlow/004 Pooling Layers.en.srt 11KB
  216. 04 Matplotlib and Visualization Overview/007 Matplotlib Styling - Legends.en.srt 11KB
  217. 08 Convolutional Neural Networks with TensorFlow/008 CNN on MNIST - Model Evaluation.en.srt 10KB
  218. 04 Matplotlib and Visualization Overview/010 Matplotlib Exercise Questions Overview.en.srt 10KB
  219. 08 Convolutional Neural Networks with TensorFlow/011 Downloading Data Set for Real Image Lectures.en.srt 9KB
  220. 12 Deep Q-Learning/014 DQN - Keras-RL2 - Part Three - Creating the ANN.en.srt 9KB
  221. 09 Reinforcement Learning - Core Concepts/004 Deterministic vs. Stochastic Processes.en.srt 8KB
  222. 04 Matplotlib and Visualization Overview/005 Matplotlib - Figure Parameters.en.srt 8KB
  223. 12 Deep Q-Learning/008 DQN Manual Implementation - Part One - Imports and Environment.en.srt 8KB
  224. 11 Classical Q Learning/014 Continuous Q-Learning Theory - Part Three - Discretization Theory.en.srt 8KB
  225. 08 Convolutional Neural Networks with TensorFlow/005 MNIST Data Set Overview.en.srt 8KB
  226. 12 Deep Q-Learning/003 DQN Theory and Intuition - Part One - Review of Core RL Ideas.en.srt 7KB
  227. 04 Matplotlib and Visualization Overview/001 Introduction to Matplotlib.en.srt 7KB
  228. 12 Deep Q-Learning/002 History of DQN.en.srt 7KB
  229. 04 Matplotlib and Visualization Overview/009 Advanced Matplotlib Commands (Optional).en.srt 7KB
  230. 11 Classical Q Learning/001 Introduction to Classical Q-Learning Overview.en.srt 6KB
  231. 07 Artificial Neural Network and TensorFlow Basics/025 Keras Project Solutions- Creating and Training the Model.en.srt 6KB
  232. 12 Deep Q-Learning/016 DQN - Exercise Overview.en.srt 6KB
  233. 11 Classical Q Learning/002 History of Q-Learning.en.srt 6KB
  234. 07 Artificial Neural Network and TensorFlow Basics/024 Keras Project Solutions - Data Preprocessing.en.srt 5KB
  235. 12 Deep Q-Learning/013 DQN - Keras-RL2 - Part Two - Imports and Environment.en.srt 5KB
  236. 06 Pandas and Scikit-Learn Crash Course/033 Advertising.csv 4KB
  237. 08 Convolutional Neural Networks with TensorFlow/016 CNN Exercise Project Overview.en.srt 4KB
  238. 07 Artificial Neural Network and TensorFlow Basics/001 Introduction to Artificial Neural Networks.en.srt 3KB
  239. 07 Artificial Neural Network and TensorFlow Basics/008 TensorFlow vs. Keras Explained.en.srt 3KB
  240. 03 Numpy Basics Overview/001 Introduction to Numpy Section.en.srt 3KB
  241. 12 Deep Q-Learning/001 DQN Section Overview.en.srt 3KB
  242. 09 Reinforcement Learning - Core Concepts/001 Overview of Core Concepts for Reinforcement Learning Section.en.srt 3KB
  243. 01 Course Overview/001 Welcome Message.html 3KB
  244. 08 Convolutional Neural Networks with TensorFlow/001 Convolutional Neural Networks Section Overview.en.srt 3KB
  245. 07 Artificial Neural Network and TensorFlow Basics/018 Keras Classification - Overview of Project Options.en.srt 3KB
  246. 03 Numpy Basics Overview/005 Numpy Exercise Overview.en.srt 2KB
  247. 10 Open AI Gym Overview/001 Introduction to OpenAI Gym Section.en.srt 2KB
  248. 02 Course Set-Up and Installation Procedures/002 Note on Environment Setup.html 2KB
  249. 06 Pandas and Scikit-Learn Crash Course/001 Pandas and Scikit-Learn Overview.html 1KB
  250. 09 Reinforcement Learning - Core Concepts/005 Tabular Reinforcement Learning.html 1KB
  251. 08 Convolutional Neural Networks with TensorFlow/external-assets-links.txt 180B