589689.xyz

[ ] Udemy - Advanced Reinforcement Learning in Python - from DQN to SAC

  • 收录时间:2022-12-24 13:45:13
  • 文件大小:2GB
  • 下载次数:1
  • 最近下载:2022-12-24 13:45:13
  • 磁力链接:
立即下载 复制链接

文件列表

  1. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/003 Create the robotics task.mp4 74MB
  2. ~Get Your Files Here !/13 - Hindsight Experience Replay/004 Implement Hindsight Experience Replay (HER) - Part 3.mp4 74MB
  3. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/007 Implement the Soft Actor-Critic algorithm - Part 2.mp4 67MB
  4. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/011 Define the training step.mp4 58MB
  5. ~Get Your Files Here !/06 - PyTorch Lightning/008 Define the class for the Deep Q-Learning algorithm.mp4 55MB
  6. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/005 Create the gradient policy.mp4 54MB
  7. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/006 Stochastic Gradient Descent.mp4 50MB
  8. ~Get Your Files Here !/06 - PyTorch Lightning/011 Define the train_step() method.mp4 50MB
  9. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/010 Creating the (NAF) Deep Q-Network 4.mp4 48MB
  10. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/006 Create the gradient policy.mp4 43MB
  11. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/015 Create the (NAF) Deep Q-Learning algorithm.mp4 43MB
  12. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/007 Creating the (NAF) Deep Q-Network 1.mp4 41MB
  13. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/006 Implement the Soft Actor-Critic algorithm - Part 1.mp4 40MB
  14. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/008 Create the DDPG class.mp4 39MB
  15. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/002 Elements common to all control tasks.mp4 39MB
  16. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/005 How to represent a Neural Network.mp4 38MB
  17. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/002 Function approximators.mp4 36MB
  18. ~Get Your Files Here !/06 - PyTorch Lightning/014 Train the Deep Q-Learning algorithm.mp4 35MB
  19. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/012 Launch the training process.mp4 34MB
  20. ~Get Your Files Here !/13 - Hindsight Experience Replay/002 Implement Hindsight Experience Replay (HER) - Part 1.mp4 34MB
  21. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/001 Twin Delayed DDPG (TD3).mp4 34MB
  22. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/003 Log average return.mp4 34MB
  23. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/001 Hyperparameter tuning with Optuna.mp4 32MB
  24. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/002 Deep Deterministic Policy Gradient (DDPG).mp4 32MB
  25. ~Get Your Files Here !/06 - PyTorch Lightning/007 Create the environment.mp4 32MB
  26. ~Get Your Files Here !/06 - PyTorch Lightning/012 Define the train_epoch_end() method.mp4 32MB
  27. ~Get Your Files Here !/06 - PyTorch Lightning/001 PyTorch Lightning.mp4 32MB
  28. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/005 Deep Deterministic Policy Gradient (DDPG).mp4 32MB
  29. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/005 Clipped double Q-Learning.mp4 32MB
  30. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/008 Check the resulting agent.mp4 31MB
  31. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/007 Target policy smoothing.mp4 31MB
  32. ~Get Your Files Here !/06 - PyTorch Lightning/003 Introduction to PyTorch Lightning.mp4 31MB
  33. ~Get Your Files Here !/06 - PyTorch Lightning/010 Prepare the data loader and the optimizer.mp4 30MB
  34. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/013 Check the resulting agent.mp4 30MB
  35. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/004 Define the objective function.mp4 30MB
  36. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/001 Continuous action spaces.mp4 30MB
  37. ~Get Your Files Here !/06 - PyTorch Lightning/009 Define the play_episode() function.mp4 29MB
  38. ~Get Your Files Here !/09 - Refresher Policy gradient methods/003 Representing policies using neural networks.mp4 28MB
  39. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/004 Artificial Neurons.mp4 26MB
  40. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/003 The Markov decision process (MDP).mp4 25MB
  41. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/011 Creating the policy.mp4 25MB
  42. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/003 Artificial Neural Networks.mp4 24MB
  43. ~Get Your Files Here !/01 - Introduction/001 Introduction.mp4 24MB
  44. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/001 Soft Actor-Critic (SAC).mp4 24MB
  45. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/007 Neural Network optimization.mp4 23MB
  46. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/004 Normalized Advantage Function pseudocode.mp4 23MB
  47. ~Get Your Files Here !/09 - Refresher Policy gradient methods/005 Entropy Regularization.mp4 23MB
  48. ~Get Your Files Here !/06 - PyTorch Lightning/006 Create the replay buffer.mp4 23MB
  49. ~Get Your Files Here !/06 - PyTorch Lightning/004 Create the Deep Q-Network.mp4 23MB
  50. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/007 Create the Deep Q-Network.mp4 23MB
  51. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/012 Create the environment.mp4 23MB
  52. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/010 Setup the optimizers and dataloader.mp4 22MB
  53. ~Get Your Files Here !/13 - Hindsight Experience Replay/003 Implement Hindsight Experience Replay (HER) - Part 2.mp4 22MB
  54. ~Get Your Files Here !/09 - Refresher Policy gradient methods/001 Policy gradient methods.mp4 22MB
  55. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/003 DDPG pseudocode.mp4 21MB
  56. ~Get Your Files Here !/06 - PyTorch Lightning/015 Explore the resulting agent.mp4 20MB
  57. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/001 The Brax Physics engine.mp4 20MB
  58. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/002 TD3 pseudocode.mp4 20MB
  59. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/018 Debugging and launching the algorithm.mp4 20MB
  60. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/004 Twin Delayed DDPG (TD3).mp4 20MB
  61. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/006 Explore the best trial.mp4 19MB
  62. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/004 Create the Deep Q-Network.mp4 19MB
  63. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/005 Create and launch the hyperparameter tuning job.mp4 19MB
  64. ~Get Your Files Here !/06 - PyTorch Lightning/005 Create the policy.mp4 18MB
  65. ~Get Your Files Here !/14 - Final steps/001 Next steps.mp4 17MB
  66. ~Get Your Files Here !/13 - Hindsight Experience Replay/001 Hindsight Experience Replay (HER).mp4 17MB
  67. ~Get Your Files Here !/05 - Refresher Deep Q-Learning/004 Target Network.mp4 17MB
  68. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/019 Checking the resulting agent.mp4 16MB
  69. ~Get Your Files Here !/05 - Refresher Deep Q-Learning/002 Deep Q-Learning.mp4 16MB
  70. ~Get Your Files Here !/09 - Refresher Policy gradient methods/004 The policy gradient theorem.mp4 16MB
  71. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/008 Creating the (NAF) Deep Q-Network 2.mp4 15MB
  72. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/007 Discount factor.mp4 15MB
  73. ~Get Your Files Here !/03 - Refresher Q-Learning/003 Solving control tasks with temporal difference methods.mp4 15MB
  74. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/011 Solving a Markov decision process.mp4 14MB
  75. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/002 The advantage function.mp4 13MB
  76. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/016 Implement the training step.mp4 13MB
  77. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/009 Define the play method.mp4 13MB
  78. ~Get Your Files Here !/03 - Refresher Q-Learning/002 Temporal difference methods.mp4 13MB
  79. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/017 Implement the end-of-epoch logic.mp4 12MB
  80. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/010 Bellman equations.mp4 12MB
  81. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/008 Check the results.mp4 12MB
  82. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/006 Delayed policy updates.mp4 12MB
  83. ~Get Your Files Here !/03 - Refresher Q-Learning/004 Q-Learning.mp4 11MB
  84. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/014 Implementing Polyak averaging.mp4 10MB
  85. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/003 Normalized Advantage Function (NAF).mp4 10MB
  86. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/002 SAC pseudocode.mp4 10MB
  87. ~Get Your Files Here !/05 - Refresher Deep Q-Learning/003 Experience Replay.mp4 9MB
  88. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/004 Types of Markov decision process.mp4 9MB
  89. ~Get Your Files Here !/09 - Refresher Policy gradient methods/002 Policy performance.mp4 9MB
  90. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/008 Policy.mp4 7MB
  91. ~Get Your Files Here !/13 - Hindsight Experience Replay/005 Check the results.mp4 7MB
  92. ~Get Your Files Here !/01 - Introduction/003 Google Colab.mp4 6MB
  93. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/009 Creating the (NAF) Deep Q-Network 3.mp4 5MB
  94. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/006 Reward vs Return.mp4 5MB
  95. ~Get Your Files Here !/01 - Introduction/004 Where to begin.mp4 5MB
  96. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/005 Trajectory vs episode.mp4 5MB
  97. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/013 Polyak averaging.mp4 5MB
  98. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/006 Hyperbolic tangent.mp4 5MB
  99. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/009 State values v(s) and action values q(s,a).mp4 4MB
  100. ~Get Your Files Here !/03 - Refresher Q-Learning/005 Advantages of temporal difference methods.mp4 4MB
  101. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/001 Module Overview.mp4 3MB
  102. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/001 Module overview.mp4 2MB
  103. ~Get Your Files Here !/03 - Refresher Q-Learning/001 Module overview.mp4 1MB
  104. ~Get Your Files Here !/05 - Refresher Deep Q-Learning/001 Module overview.mp4 1MB
  105. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/005 Create the gradient policy_en.vtt 13KB
  106. ~Get Your Files Here !/06 - PyTorch Lightning/008 Define the class for the Deep Q-Learning algorithm_en.vtt 12KB
  107. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/003 Create the robotics task_en.vtt 11KB
  108. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/001 Twin Delayed DDPG (TD3)_en.vtt 11KB
  109. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/002 Deep Deterministic Policy Gradient (DDPG)_en.vtt 10KB
  110. ~Get Your Files Here !/13 - Hindsight Experience Replay/004 Implement Hindsight Experience Replay (HER) - Part 3_en.vtt 10KB
  111. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/011 Define the training step_en.vtt 10KB
  112. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/006 Create the gradient policy_en.vtt 10KB
  113. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/001 Hyperparameter tuning with Optuna_en.vtt 10KB
  114. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/010 Creating the (NAF) Deep Q-Network 4_en.vtt 9KB
  115. ~Get Your Files Here !/06 - PyTorch Lightning/011 Define the train_step() method_en.vtt 9KB
  116. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/007 Implement the Soft Actor-Critic algorithm - Part 2_en.vtt 9KB
  117. ~Get Your Files Here !/06 - PyTorch Lightning/001 PyTorch Lightning_en.vtt 9KB
  118. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/002 Function approximators_en.vtt 8KB
  119. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/015 Create the (NAF) Deep Q-Learning algorithm_en.vtt 8KB
  120. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/001 Soft Actor-Critic (SAC)_en.vtt 7KB
  121. ~Get Your Files Here !/06 - PyTorch Lightning/007 Create the environment_en.vtt 7KB
  122. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/007 Creating the (NAF) Deep Q-Network 1_en.vtt 7KB
  123. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/008 Create the DDPG class_en.vtt 7KB
  124. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/005 How to represent a Neural Network_en.vtt 7KB
  125. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/006 Implement the Soft Actor-Critic algorithm - Part 1_en.vtt 7KB
  126. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/001 Continuous action spaces_en.vtt 7KB
  127. ~Get Your Files Here !/09 - Refresher Policy gradient methods/005 Entropy Regularization_en.vtt 7KB
  128. ~Get Your Files Here !/06 - PyTorch Lightning/014 Train the Deep Q-Learning algorithm_en.vtt 6KB
  129. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/006 Stochastic Gradient Descent_en.vtt 6KB
  130. ~Get Your Files Here !/06 - PyTorch Lightning/003 Introduction to PyTorch Lightning_en.vtt 6KB
  131. ~Get Your Files Here !/01 - Introduction/001 Introduction_en.vtt 6KB
  132. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/002 Elements common to all control tasks_en.vtt 6KB
  133. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/004 Artificial Neurons_en.vtt 6KB
  134. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/004 Normalized Advantage Function pseudocode_en.vtt 6KB
  135. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/005 Deep Deterministic Policy Gradient (DDPG)_en.vtt 6KB
  136. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/003 The Markov decision process (MDP)_en.vtt 6KB
  137. ~Get Your Files Here !/06 - PyTorch Lightning/006 Create the replay buffer_en.vtt 6KB
  138. ~Get Your Files Here !/09 - Refresher Policy gradient methods/003 Representing policies using neural networks_en.vtt 5KB
  139. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/004 Define the objective function_en.vtt 5KB
  140. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/011 Creating the policy_en.vtt 5KB
  141. ~Get Your Files Here !/13 - Hindsight Experience Replay/002 Implement Hindsight Experience Replay (HER) - Part 1_en.vtt 5KB
  142. ~Get Your Files Here !/06 - PyTorch Lightning/004 Create the Deep Q-Network_en.vtt 5KB
  143. ~Get Your Files Here !/06 - PyTorch Lightning/005 Create the policy_en.vtt 5KB
  144. ~Get Your Files Here !/06 - PyTorch Lightning/009 Define the play_episode() function_en.vtt 5KB
  145. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/002 The advantage function_en.vtt 5KB
  146. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/003 Log average return_en.vtt 5KB
  147. ~Get Your Files Here !/09 - Refresher Policy gradient methods/001 Policy gradient methods_en.vtt 5KB
  148. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/012 Create the environment_en.vtt 5KB
  149. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/007 Neural Network optimization_en.vtt 4KB
  150. ~Get Your Files Here !/13 - Hindsight Experience Replay/001 Hindsight Experience Replay (HER)_en.vtt 4KB
  151. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/007 Create the Deep Q-Network_en.vtt 4KB
  152. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/002 TD3 pseudocode_en.vtt 4KB
  153. ~Get Your Files Here !/06 - PyTorch Lightning/010 Prepare the data loader and the optimizer_en.vtt 4KB
  154. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/007 Target policy smoothing_en.vtt 4KB
  155. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/007 Discount factor_en.vtt 4KB
  156. ~Get Your Files Here !/06 - PyTorch Lightning/012 Define the train_epoch_end() method_en.vtt 4KB
  157. ~Get Your Files Here !/05 - Refresher Deep Q-Learning/004 Target Network_en.vtt 4KB
  158. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/003 DDPG pseudocode_en.vtt 4KB
  159. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/005 Clipped double Q-Learning_en.vtt 4KB
  160. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/012 Launch the training process_en.vtt 4KB
  161. ~Get Your Files Here !/09 - Refresher Policy gradient methods/004 The policy gradient theorem_en.vtt 4KB
  162. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/003 Artificial Neural Networks_en.vtt 4KB
  163. ~Get Your Files Here !/03 - Refresher Q-Learning/003 Solving control tasks with temporal difference methods_en.vtt 4KB
  164. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/004 Create the Deep Q-Network_en.vtt 4KB
  165. ~Get Your Files Here !/03 - Refresher Q-Learning/002 Temporal difference methods_en.vtt 3KB
  166. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/001 The Brax Physics engine_en.vtt 3KB
  167. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/003 Normalized Advantage Function (NAF)_en.vtt 3KB
  168. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/008 Creating the (NAF) Deep Q-Network 2_en.vtt 3KB
  169. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/004 Twin Delayed DDPG (TD3)_en.vtt 3KB
  170. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/010 Setup the optimizers and dataloader_en.vtt 3KB
  171. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/011 Solving a Markov decision process_en.vtt 3KB
  172. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/010 Bellman equations_en.vtt 3KB
  173. ~Get Your Files Here !/13 - Hindsight Experience Replay/003 Implement Hindsight Experience Replay (HER) - Part 2_en.vtt 3KB
  174. ~Get Your Files Here !/05 - Refresher Deep Q-Learning/002 Deep Q-Learning_en.vtt 3KB
  175. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/018 Debugging and launching the algorithm_en.vtt 3KB
  176. ~Get Your Files Here !/06 - PyTorch Lightning/015 Explore the resulting agent_en.vtt 3KB
  177. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/005 Create and launch the hyperparameter tuning job_en.vtt 3KB
  178. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/006 Explore the best trial_en.vtt 3KB
  179. ~Get Your Files Here !/09 - Refresher Policy gradient methods/002 Policy performance_en.vtt 3KB
  180. ~Get Your Files Here !/03 - Refresher Q-Learning/004 Q-Learning_en.vtt 2KB
  181. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/016 Implement the training step_en.vtt 2KB
  182. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/008 Check the resulting agent_en.vtt 2KB
  183. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/004 Types of Markov decision process_en.vtt 2KB
  184. ~Get Your Files Here !/05 - Refresher Deep Q-Learning/003 Experience Replay_en.vtt 2KB
  185. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/017 Implement the end-of-epoch logic_en.vtt 2KB
  186. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/014 Implementing Polyak averaging_en.vtt 2KB
  187. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/008 Policy_en.vtt 2KB
  188. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/009 Define the play method_en.vtt 2KB
  189. ~Get Your Files Here !/14 - Final steps/001 Next steps_en.vtt 2KB
  190. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/008 Check the results_en.vtt 2KB
  191. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/006 Delayed policy updates_en.vtt 2KB
  192. ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/002 SAC pseudocode_en.vtt 2KB
  193. ~Get Your Files Here !/01 - Introduction/004 Where to begin_en.vtt 2KB
  194. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/019 Checking the resulting agent_en.vtt 2KB
  195. ~Get Your Files Here !/01 - Introduction/003 Google Colab_en.vtt 2KB
  196. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/013 Check the resulting agent_en.vtt 2KB
  197. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/006 Reward vs Return_en.vtt 2KB
  198. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/006 Hyperbolic tangent_en.vtt 2KB
  199. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/013 Polyak averaging_en.vtt 1KB
  200. ~Get Your Files Here !/03 - Refresher Q-Learning/005 Advantages of temporal difference methods_en.vtt 1KB
  201. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/009 State values v(s) and action values q(s,a)_en.vtt 1KB
  202. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/009 Creating the (NAF) Deep Q-Network 3_en.vtt 1KB
  203. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/005 Trajectory vs episode_en.vtt 1KB
  204. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/001 Module Overview_en.vtt 1KB
  205. ~Get Your Files Here !/13 - Hindsight Experience Replay/005 Check the results_en.vtt 1003B
  206. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/001 Module overview_en.vtt 739B
  207. ~Get Your Files Here !/03 - Refresher Q-Learning/001 Module overview_en.vtt 720B
  208. ~Get Your Files Here !/06 - PyTorch Lightning/013 [Important] Lecture correction.html 613B
  209. ~Get Your Files Here !/05 - Refresher Deep Q-Learning/001 Module overview_en.vtt 551B
  210. ~Get Your Files Here !/01 - Introduction/002 Reinforcement Learning series.html 491B
  211. ~Get Your Files Here !/14 - Final steps/002 Next steps.html 480B
  212. ~Get Your Files Here !/Bonus Resources.txt 386B
  213. ~Get Your Files Here !/06 - PyTorch Lightning/002 Link to the code notebook.html 280B
  214. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/002 Link to the code notebook.html 280B
  215. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/005 Link to the code notebook.html 280B
  216. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/004 Link to the code notebook.html 280B
  217. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/003 Link to code notebook.html 280B
  218. Get Bonus Downloads Here.url 182B
  219. ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/external-assets-links.txt 153B
  220. ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/external-assets-links.txt 148B
  221. ~Get Your Files Here !/01 - Introduction/external-assets-links.txt 144B
  222. ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/external-assets-links.txt 144B
  223. ~Get Your Files Here !/03 - Refresher Q-Learning/external-assets-links.txt 144B
  224. ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/external-assets-links.txt 144B
  225. ~Get Your Files Here !/05 - Refresher Deep Q-Learning/external-assets-links.txt 144B
  226. ~Get Your Files Here !/06 - PyTorch Lightning/external-assets-links.txt 140B
  227. ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/external-assets-links.txt 140B
  228. ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/external-assets-links.txt 136B