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[ DevCourseWeb.com ] Udemy - Advanced Reinforcement Learning in Python - from DQN to SAC
magnet:?xt=urn:btih:e1676bd24ed4f26da6dfdb9d5274227b5427af5c&dn=[ DevCourseWeb.com ] Udemy - Advanced Reinforcement Learning in Python - from DQN to SAC
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e1676bd24ed4f26da6dfdb9d5274227b5427af5c
infohash:
104
文件数量
2.42 GB
文件大小
2023-12-29 02:50
创建日期
2024-11-11 18:32
最后访问
相关分词
DevCourseWeb
com
Udemy
-
Advanced
Reinforcement
Learning
in
Python
-
from
DQN
to
SAC
~Get Your Files Here !/01 - Introduction/001 Introduction.mp4 24.29 MB
~Get Your Files Here !/01 - Introduction/003 Google Colab.mp4 5.77 MB
~Get Your Files Here !/01 - Introduction/004 Where to begin.mp4 5.06 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/001 Module Overview.mp4 2.61 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/002 Elements common to all control tasks.mp4 38.74 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/003 The Markov decision process (MDP).mp4 25.1 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/004 Types of Markov decision process.mp4 8.68 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/005 Trajectory vs episode.mp4 4.94 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/006 Reward vs Return.mp4 5.28 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/007 Discount factor.mp4 14.77 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/008 Policy.mp4 7.41 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/009 State values v(s) and action values q(s,a).mp4 4.28 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/010 Bellman equations.mp4 12.41 MB
~Get Your Files Here !/02 - Refresher The Markov Decision Process (MDP)/011 Solving a Markov decision process.mp4 14.14 MB
~Get Your Files Here !/03 - Refresher Q-Learning/001 Module overview.mp4 1.49 MB
~Get Your Files Here !/03 - Refresher Q-Learning/002 Temporal difference methods.mp4 12.62 MB
~Get Your Files Here !/03 - Refresher Q-Learning/003 Solving control tasks with temporal difference methods.mp4 14.52 MB
~Get Your Files Here !/03 - Refresher Q-Learning/004 Q-Learning.mp4 11.08 MB
~Get Your Files Here !/03 - Refresher Q-Learning/005 Advantages of temporal difference methods.mp4 3.71 MB
~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/001 Module overview.mp4 1.78 MB
~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/002 Function approximators.mp4 36.32 MB
~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/003 Artificial Neural Networks.mp4 24.34 MB
~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/004 Artificial Neurons.mp4 25.64 MB
~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/005 How to represent a Neural Network.mp4 38.16 MB
~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/006 Stochastic Gradient Descent.mp4 49.87 MB
~Get Your Files Here !/04 - Refresher Brief introduction to Neural Networks/007 Neural Network optimization.mp4 23.39 MB
~Get Your Files Here !/05 - Refresher Deep Q-Learning/001 Module overview.mp4 1.27 MB
~Get Your Files Here !/05 - Refresher Deep Q-Learning/002 Deep Q-Learning.mp4 16.17 MB
~Get Your Files Here !/05 - Refresher Deep Q-Learning/003 Experience Replay.mp4 8.98 MB
~Get Your Files Here !/05 - Refresher Deep Q-Learning/004 Target Network.mp4 16.57 MB
~Get Your Files Here !/06 - PyTorch Lightning/001 PyTorch Lightning.mp4 32 MB
~Get Your Files Here !/06 - PyTorch Lightning/003 Introduction to PyTorch Lightning.mp4 30.93 MB
~Get Your Files Here !/06 - PyTorch Lightning/004 Create the Deep Q-Network.mp4 22.93 MB
~Get Your Files Here !/06 - PyTorch Lightning/005 Create the policy.mp4 18.04 MB
~Get Your Files Here !/06 - PyTorch Lightning/006 Create the replay buffer.mp4 22.98 MB
~Get Your Files Here !/06 - PyTorch Lightning/007 Create the environment.mp4 32.22 MB
~Get Your Files Here !/06 - PyTorch Lightning/008 Define the class for the Deep Q-Learning algorithm.mp4 54.54 MB
~Get Your Files Here !/06 - PyTorch Lightning/009 Define the play_episode() function.mp4 29.1 MB
~Get Your Files Here !/06 - PyTorch Lightning/010 Prepare the data loader and the optimizer.mp4 30.43 MB
~Get Your Files Here !/06 - PyTorch Lightning/011 Define the train_step() method.mp4 49.77 MB
~Get Your Files Here !/06 - PyTorch Lightning/012 Define the train_epoch_end() method.mp4 32.17 MB
~Get Your Files Here !/06 - PyTorch Lightning/014 Train the Deep Q-Learning algorithm.mp4 35.03 MB
~Get Your Files Here !/06 - PyTorch Lightning/015 Explore the resulting agent.mp4 20.26 MB
~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/001 Hyperparameter tuning with Optuna.mp4 32.42 MB
~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/003 Log average return.mp4 33.62 MB
~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/004 Define the objective function.mp4 29.84 MB
~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/005 Create and launch the hyperparameter tuning job.mp4 18.5 MB
~Get Your Files Here !/07 - Hyperparameter tuning with Optuna/006 Explore the best trial.mp4 19.15 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/001 Continuous action spaces.mp4 29.64 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/002 The advantage function.mp4 13.42 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/003 Normalized Advantage Function (NAF).mp4 10.09 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/004 Normalized Advantage Function pseudocode.mp4 23.16 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/006 Hyperbolic tangent.mp4 4.68 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 41.41 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 15.01 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 5.38 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 47.88 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/011 Creating the policy.mp4 25.04 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/012 Create the environment.mp4 22.51 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/013 Polyak averaging.mp4 4.82 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/014 Implementing Polyak averaging.mp4 10.35 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 42.87 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/016 Implement the training step.mp4 13.27 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/017 Implement the end-of-epoch logic.mp4 12.49 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/018 Debugging and launching the algorithm.mp4 19.98 MB
~Get Your Files Here !/08 - Deep Q-Learning for continuous action spaces (Normalized Advantage Function)/019 Checking the resulting agent.mp4 16.42 MB
~Get Your Files Here !/09 - Refresher Policy gradient methods/001 Policy gradient methods.mp4 21.65 MB
~Get Your Files Here !/09 - Refresher Policy gradient methods/002 Policy performance.mp4 8.52 MB
~Get Your Files Here !/09 - Refresher Policy gradient methods/003 Representing policies using neural networks.mp4 27.76 MB
~Get Your Files Here !/09 - Refresher Policy gradient methods/004 The policy gradient theorem.mp4 15.89 MB
~Get Your Files Here !/09 - Refresher Policy gradient methods/005 Entropy Regularization.mp4 23.15 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/001 The Brax Physics engine.mp4 20.05 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/002 Deep Deterministic Policy Gradient (DDPG).mp4 32.33 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/003 DDPG pseudocode.mp4 20.92 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/005 Deep Deterministic Policy Gradient (DDPG).mp4 31.81 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/006 Create the gradient policy.mp4 43.44 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/007 Create the Deep Q-Network.mp4 22.77 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/008 Create the DDPG class.mp4 38.86 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/009 Define the play method.mp4 13.23 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/010 Setup the optimizers and dataloader.mp4 22.25 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/011 Define the training step.mp4 57.89 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/012 Launch the training process.mp4 34.2 MB
~Get Your Files Here !/10 - Deep Deterministic Policy Gradient (DDPG)/013 Check the resulting agent.mp4 30.24 MB
~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/001 Twin Delayed DDPG (TD3).mp4 33.96 MB
~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/002 TD3 pseudocode.mp4 20.01 MB
~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/004 Twin Delayed DDPG (TD3).mp4 19.95 MB
~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/005 Clipped double Q-Learning.mp4 31.52 MB
~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/006 Delayed policy updates.mp4 12.07 MB
~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/007 Target policy smoothing.mp4 30.96 MB
~Get Your Files Here !/11 - Twin Delayed DDPG (TD3)/008 Check the resulting agent.mp4 31.09 MB
~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/001 Soft Actor-Critic (SAC).mp4 23.96 MB
~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/002 SAC pseudocode.mp4 9.5 MB
~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/003 Create the robotics task.mp4 74.02 MB
~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/004 Create the Deep Q-Network.mp4 18.98 MB
~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/005 Create the gradient policy.mp4 53.76 MB
~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/006 Implement the Soft Actor-Critic algorithm - Part 1.mp4 40.06 MB
~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/007 Implement the Soft Actor-Critic algorithm - Part 2.mp4 66.71 MB
~Get Your Files Here !/12 - Soft Actor-Critic (SAC)/008 Check the results.mp4 12.09 MB
~Get Your Files Here !/13 - Hindsight Experience Replay/001 Hindsight Experience Replay (HER).mp4 17.07 MB
~Get Your Files Here !/13 - Hindsight Experience Replay/002 Implement Hindsight Experience Replay (HER) - Part 1.mp4 33.98 MB
~Get Your Files Here !/13 - Hindsight Experience Replay/003 Implement Hindsight Experience Replay (HER) - Part 2.mp4 21.66 MB
~Get Your Files Here !/13 - Hindsight Experience Replay/004 Implement Hindsight Experience Replay (HER) - Part 3.mp4 73.74 MB
~Get Your Files Here !/13 - Hindsight Experience Replay/005 Check the results.mp4 7.4 MB
~Get Your Files Here !/14 - Final steps/001 Next steps.mp4 17.27 MB
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