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

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

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收录时间：2023-12-29
最近下载：2025-05-31

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文件列表

  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/003 Create the robotics task.mp4 77.6 MB
  • ~Get Your Files Here !/13 - Hindsight Experience Replay/004 Implement Hindsight Experience Replay (HER) - Part 3.mp4 77.3 MB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/007 Implement the Soft Actor-Critic algorithm - Part 2.mp4 69.9 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/011 Define the training step.mp4 60.7 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/008 Define the class for the Deep Q-Learning algorithm.mp4 57.2 MB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/005 Create the gradient policy.mp4 56.4 MB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/006 Stochastic Gradient Descent.mp4 52.3 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/011 Define the train_step() method.mp4 52.2 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/010 Creating the (NAF) Deep Q-Network 4.mp4 50.2 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/006 Create the gradient policy.mp4 45.6 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/015 Create the (NAF) Deep Q-Learning algorithm.mp4 45.0 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/007 Creating the (NAF) Deep Q-Network 1.mp4 43.4 MB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/006 Implement the Soft Actor-Critic algorithm - Part 1.mp4 42.0 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/008 Create the DDPG class.mp4 40.7 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/002 Elements common to all control tasks.mp4 40.6 MB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/005 How to represent a Neural Network.mp4 40.0 MB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/002 Function approximators.mp4 38.1 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/014 Train the Deep Q-Learning algorithm.mp4 36.7 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/012 Launch the training process.mp4 35.9 MB
  • ~Get Your Files Here !/13 - Hindsight Experience Replay/002 Implement Hindsight Experience Replay (HER) - Part 1.mp4 35.6 MB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/001 Twin Delayed DDPG (TD3).mp4 35.6 MB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/003 Log average return.mp4 35.3 MB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/001 Hyperparameter tuning with Optuna.mp4 34.0 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/002 Deep Deterministic Policy Gradient (DDPG).mp4 33.9 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/007 Create the environment.mp4 33.8 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/012 Define the train_epoch_end() method.mp4 33.7 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/001 PyTorch Lightning.mp4 33.6 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/005 Deep Deterministic Policy Gradient (DDPG).mp4 33.4 MB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/005 Clipped double Q-Learning.mp4 33.1 MB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/008 Check the resulting agent.mp4 32.6 MB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/007 Target policy smoothing.mp4 32.5 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/003 Introduction to PyTorch Lightning.mp4 32.4 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/010 Prepare the data loader and the optimizer.mp4 31.9 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/013 Check the resulting agent.mp4 31.7 MB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/004 Define the objective function.mp4 31.3 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/001 Continuous action spaces.mp4 31.1 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/009 Define the play_episode() function.mp4 30.5 MB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/003 Representing policies using neural networks.mp4 29.1 MB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/004 Artificial Neurons.mp4 26.9 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/003 The Markov decision process (MDP).mp4 26.3 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/011 Creating the policy.mp4 26.3 MB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/003 Artificial Neural Networks.mp4 25.5 MB
  • ~Get Your Files Here !/01 - Introduction/001 Introduction.mp4 25.5 MB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/001 Soft Actor-Critic (SAC).mp4 25.1 MB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/007 Neural Network optimization.mp4 24.5 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/004 Normalized Advantage Function pseudocode.mp4 24.3 MB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/005 Entropy Regularization.mp4 24.3 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/006 Create the replay buffer.mp4 24.1 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/004 Create the Deep Q-Network.mp4 24.0 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/007 Create the Deep Q-Network.mp4 23.9 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/012 Create the environment.mp4 23.6 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/010 Setup the optimizers and dataloader.mp4 23.3 MB
  • ~Get Your Files Here !/13 - Hindsight Experience Replay/003 Implement Hindsight Experience Replay (HER) - Part 2.mp4 22.7 MB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/001 Policy gradient methods.mp4 22.7 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/003 DDPG pseudocode.mp4 21.9 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/015 Explore the resulting agent.mp4 21.2 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/001 The Brax Physics engine.mp4 21.0 MB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/002 TD3 pseudocode.mp4 21.0 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/018 Debugging and launching the algorithm.mp4 21.0 MB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/004 Twin Delayed DDPG (TD3).mp4 20.9 MB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/006 Explore the best trial.mp4 20.1 MB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/004 Create the Deep Q-Network.mp4 19.9 MB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/005 Create and launch the hyperparameter tuning job.mp4 19.4 MB
  • ~Get Your Files Here !/06 - PyTorch Lightning/005 Create the policy.mp4 18.9 MB
  • ~Get Your Files Here !/14 - Final steps/001 Next steps.mp4 18.1 MB
  • ~Get Your Files Here !/13 - Hindsight Experience Replay/001 Hindsight Experience Replay (HER).mp4 17.9 MB
  • ~Get Your Files Here !/05 - Refresher Deep Q-Learning/004 Target Network.mp4 17.4 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/019 Checking the resulting agent.mp4 17.2 MB
  • ~Get Your Files Here !/05 - Refresher Deep Q-Learning/002 Deep Q-Learning.mp4 17.0 MB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/004 The policy gradient theorem.mp4 16.7 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/008 Creating the (NAF) Deep Q-Network 2.mp4 15.7 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/007 Discount factor.mp4 15.5 MB
  • ~Get Your Files Here !/03 - Refresher Q-Learning/003 Solving control tasks with temporal difference methods.mp4 15.2 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/011 Solving a Markov decision process.mp4 14.8 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/002 The advantage function.mp4 14.1 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/016 Implement the training step.mp4 13.9 MB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/009 Define the play method.mp4 13.9 MB
  • ~Get Your Files Here !/03 - Refresher Q-Learning/002 Temporal difference methods.mp4 13.2 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/017 Implement the end-of-epoch logic.mp4 13.1 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/010 Bellman equations.mp4 13.0 MB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/008 Check the results.mp4 12.7 MB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/006 Delayed policy updates.mp4 12.7 MB
  • ~Get Your Files Here !/03 - Refresher Q-Learning/004 Q-Learning.mp4 11.6 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/014 Implementing Polyak averaging.mp4 10.9 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/003 Normalized Advantage Function (NAF).mp4 10.6 MB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/002 SAC pseudocode.mp4 10.0 MB
  • ~Get Your Files Here !/05 - Refresher Deep Q-Learning/003 Experience Replay.mp4 9.4 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/004 Types of Markov decision process.mp4 9.1 MB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/002 Policy performance.mp4 8.9 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/008 Policy.mp4 7.8 MB
  • ~Get Your Files Here !/13 - Hindsight Experience Replay/005 Check the results.mp4 7.8 MB
  • ~Get Your Files Here !/01 - Introduction/003 Google Colab.mp4 6.1 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/009 Creating the (NAF) Deep Q-Network 3.mp4 5.6 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/006 Reward vs Return.mp4 5.5 MB
  • ~Get Your Files Here !/01 - Introduction/004 Where to begin.mp4 5.3 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/005 Trajectory vs episode.mp4 5.2 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/013 Polyak averaging.mp4 5.1 MB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/006 Hyperbolic tangent.mp4 4.9 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/009 State values v(s) and action values q(s,a).mp4 4.5 MB
  • ~Get Your Files Here !/03 - Refresher Q-Learning/005 Advantages of temporal difference methods.mp4 3.9 MB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/001 Module Overview.mp4 2.7 MB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/001 Module overview.mp4 1.9 MB
  • ~Get Your Files Here !/03 - Refresher Q-Learning/001 Module overview.mp4 1.6 MB
  • ~Get Your Files Here !/05 - Refresher Deep Q-Learning/001 Module overview.mp4 1.3 MB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/005 Create the gradient policy_en.vtt 12.9 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/008 Define the class for the Deep Q-Learning algorithm_en.vtt 11.9 kB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/003 Create the robotics task_en.vtt 11.7 kB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/001 Twin Delayed DDPG (TD3)_en.vtt 11.7 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/002 Deep Deterministic Policy Gradient (DDPG)_en.vtt 10.2 kB
  • ~Get Your Files Here !/13 - Hindsight Experience Replay/004 Implement Hindsight Experience Replay (HER) - Part 3_en.vtt 10.1 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/011 Define the training step_en.vtt 10.1 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/006 Create the gradient policy_en.vtt 10.0 kB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/001 Hyperparameter tuning with Optuna_en.vtt 9.9 kB
  • ~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 9.5 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/011 Define the train_step() method_en.vtt 9.5 kB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/007 Implement the Soft Actor-Critic algorithm - Part 2_en.vtt 9.5 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/001 PyTorch Lightning_en.vtt 9.4 kB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/002 Function approximators_en.vtt 8.7 kB
  • ~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 8.1 kB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/001 Soft Actor-Critic (SAC)_en.vtt 7.7 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/007 Create the environment_en.vtt 7.7 kB
  • ~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 7.6 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/008 Create the DDPG class_en.vtt 7.5 kB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/005 How to represent a Neural Network_en.vtt 7.4 kB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/006 Implement the Soft Actor-Critic algorithm - Part 1_en.vtt 7.3 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/001 Continuous action spaces_en.vtt 6.9 kB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/005 Entropy Regularization_en.vtt 6.7 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/014 Train the Deep Q-Learning algorithm_en.vtt 6.6 kB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/006 Stochastic Gradient Descent_en.vtt 6.5 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/003 Introduction to PyTorch Lightning_en.vtt 6.4 kB
  • ~Get Your Files Here !/01 - Introduction/001 Introduction_en.vtt 6.3 kB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/002 Elements common to all control tasks_en.vtt 6.1 kB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/004 Artificial Neurons_en.vtt 6.0 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/004 Normalized Advantage Function pseudocode_en.vtt 5.9 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/005 Deep Deterministic Policy Gradient (DDPG)_en.vtt 5.8 kB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/003 The Markov decision process (MDP)_en.vtt 5.8 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/006 Create the replay buffer_en.vtt 5.8 kB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/003 Representing policies using neural networks_en.vtt 5.4 kB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/004 Define the objective function_en.vtt 5.4 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/011 Creating the policy_en.vtt 5.3 kB
  • ~Get Your Files Here !/13 - Hindsight Experience Replay/002 Implement Hindsight Experience Replay (HER) - Part 1_en.vtt 5.3 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/004 Create the Deep Q-Network_en.vtt 5.3 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/005 Create the policy_en.vtt 5.2 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/009 Define the play_episode() function_en.vtt 5.0 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/002 The advantage function_en.vtt 4.9 kB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/003 Log average return_en.vtt 4.9 kB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/001 Policy gradient methods_en.vtt 4.9 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/012 Create the environment_en.vtt 4.7 kB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/007 Neural Network optimization_en.vtt 4.5 kB
  • ~Get Your Files Here !/13 - Hindsight Experience Replay/001 Hindsight Experience Replay (HER)_en.vtt 4.4 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/007 Create the Deep Q-Network_en.vtt 4.4 kB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/002 TD3 pseudocode_en.vtt 4.4 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/010 Prepare the data loader and the optimizer_en.vtt 4.3 kB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/007 Target policy smoothing_en.vtt 4.2 kB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/007 Discount factor_en.vtt 4.1 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/012 Define the train_epoch_end() method_en.vtt 4.1 kB
  • ~Get Your Files Here !/05 - Refresher Deep Q-Learning/004 Target Network_en.vtt 4.0 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/003 DDPG pseudocode_en.vtt 4.0 kB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/005 Clipped double Q-Learning_en.vtt 4.0 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/012 Launch the training process_en.vtt 4.0 kB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/004 The policy gradient theorem_en.vtt 3.9 kB
  • ~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/003 Artificial Neural Networks_en.vtt 3.9 kB
  • ~Get Your Files Here !/03 - Refresher Q-Learning/003 Solving control tasks with temporal difference methods_en.vtt 3.7 kB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/004 Create the Deep Q-Network_en.vtt 3.6 kB
  • ~Get Your Files Here !/03 - Refresher Q-Learning/002 Temporal difference methods_en.vtt 3.6 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/001 The Brax Physics engine_en.vtt 3.6 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/003 Normalized Advantage Function (NAF)_en.vtt 3.4 kB
  • ~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 3.3 kB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/004 Twin Delayed DDPG (TD3)_en.vtt 3.3 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/010 Setup the optimizers and dataloader_en.vtt 3.3 kB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/011 Solving a Markov decision process_en.vtt 3.2 kB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/010 Bellman equations_en.vtt 3.1 kB
  • ~Get Your Files Here !/13 - Hindsight Experience Replay/003 Implement Hindsight Experience Replay (HER) - Part 2_en.vtt 3.0 kB
  • ~Get Your Files Here !/05 - Refresher Deep Q-Learning/002 Deep Q-Learning_en.vtt 3.0 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/018 Debugging and launching the algorithm_en.vtt 2.9 kB
  • ~Get Your Files Here !/06 - PyTorch Lightning/015 Explore the resulting agent_en.vtt 2.9 kB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/005 Create and launch the hyperparameter tuning job_en.vtt 2.7 kB
  • ~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/006 Explore the best trial_en.vtt 2.7 kB
  • ~Get Your Files Here !/09 - Refresher Policy gradient methods/002 Policy performance_en.vtt 2.6 kB
  • ~Get Your Files Here !/03 - Refresher Q-Learning/004 Q-Learning_en.vtt 2.5 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/016 Implement the training step_en.vtt 2.5 kB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/008 Check the resulting agent_en.vtt 2.3 kB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/004 Types of Markov decision process_en.vtt 2.3 kB
  • ~Get Your Files Here !/05 - Refresher Deep Q-Learning/003 Experience Replay_en.vtt 2.3 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/017 Implement the end-of-epoch logic_en.vtt 2.3 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/014 Implementing Polyak averaging_en.vtt 2.3 kB
  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/008 Policy_en.vtt 2.2 kB
  • ~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/009 Define the play method_en.vtt 2.2 kB
  • ~Get Your Files Here !/14 - Final steps/001 Next steps_en.vtt 2.2 kB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/008 Check the results_en.vtt 2.2 kB
  • ~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/006 Delayed policy updates_en.vtt 2.1 kB
  • ~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/002 SAC pseudocode_en.vtt 2.1 kB
  • ~Get Your Files Here !/01 - Introduction/004 Where to begin_en.vtt 2.0 kB
  • ~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/019 Checking the resulting agent_en.vtt 2.0 kB
  • ~Get Your Files Here !/01 - Introduction/003 Google Colab_en.vtt 1.8 kB
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  • ~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/006 Reward vs Return_en.vtt 1.7 kB
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