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[ DevCourseWeb.com ] Udemy - Advanced Reinforcement Learning in Python - cutting-edge DQNs
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[ DevCourseWeb.com ] Udemy - Advanced Reinforcement Learning in Python - cutting-edge DQNs
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最近下载:
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文件列表
~Get Your Files Here !/10. Prioritized Experience Replay/3. DQN for visual inputs.mp4
72.5 MB
~Get Your Files Here !/10. Prioritized Experience Replay/4. Prioritized Experience Repay Buffer.mp4
66.7 MB
~Get Your Files Here !/10. Prioritized Experience Replay/6. Implement the Deep Q-Learning algorithm with Prioritized Experience Replay.mp4
66.4 MB
~Get Your Files Here !/10. Prioritized Experience Replay/5. Create the environment.mp4
65.6 MB
~Get Your Files Here !/6. PyTorch Lightning/8. Define the class for the Deep Q-Learning algorithm.mp4
57.2 MB
~Get Your Files Here !/9. Dueling Deep Q-Networks/3. Create the dueling DQN.mp4
57.0 MB
~Get Your Files Here !/8. Double Deep Q-Learning/3. Create the Double Deep Q-Learning algorithm.mp4
52.4 MB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/6. Stochastic Gradient Descent.mp4
52.3 MB
~Get Your Files Here !/6. PyTorch Lightning/11. Define the train_step() method.mp4
52.2 MB
~Get Your Files Here !/10. Prioritized Experience Replay/7. Launch the training process.mp4
44.6 MB
~Get Your Files Here !/9. Dueling Deep Q-Networks/4. Create the environment - Part 1.mp4
43.3 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/2. Elements common to all control tasks.mp4
40.6 MB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/5. How to represent a Neural Network.mp4
40.0 MB
~Get Your Files Here !/9. Dueling Deep Q-Networks/5. Create the environment - Part 2.mp4
38.4 MB
~Get Your Files Here !/9. Dueling Deep Q-Networks/6. Implement Deep Q-Learning.mp4
38.2 MB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/2. Function approximators.mp4
38.1 MB
~Get Your Files Here !/6. PyTorch Lightning/13. Train the Deep Q-Learning algorithm.mp4
36.8 MB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/3. Log average return.mp4
35.3 MB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/1. Hyperparameter tuning with Optuna.mp4
34.0 MB
~Get Your Files Here !/1. Introduction/1. Introduction.mp4
33.9 MB
~Get Your Files Here !/6. PyTorch Lightning/7. Create the environment.mp4
33.8 MB
~Get Your Files Here !/6. PyTorch Lightning/12. Define the train_epoch_end() method.mp4
33.7 MB
~Get Your Files Here !/6. PyTorch Lightning/1. PyTorch Lightning.mp4
33.6 MB
~Get Your Files Here !/6. PyTorch Lightning/3. Introduction to PyTorch Lightning.mp4
32.4 MB
~Get Your Files Here !/6. PyTorch Lightning/10. Prepare the data loader and the optimizer.mp4
31.9 MB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/4. Define the objective function.mp4
31.3 MB
~Get Your Files Here !/6. PyTorch Lightning/9. Define the play_episode() function.mp4
30.5 MB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/4. Artificial Neurons.mp4
26.9 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/3. The Markov decision process (MDP).mp4
26.3 MB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/3. Artificial Neural Networks.mp4
25.5 MB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/7. Neural Network optimization.mp4
24.5 MB
~Get Your Files Here !/6. PyTorch Lightning/6. Create the replay buffer.mp4
24.1 MB
~Get Your Files Here !/6. PyTorch Lightning/4. Create the Deep Q-Network.mp4
24.0 MB
~Get Your Files Here !/9. Dueling Deep Q-Networks/7. Check the resulting agent.mp4
22.0 MB
~Get Your Files Here !/6. PyTorch Lightning/14. Explore the resulting agent.mp4
21.3 MB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/6. Explore the best trial.mp4
20.1 MB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/5. Create and launch the hyperparameter tuning job.mp4
19.4 MB
~Get Your Files Here !/6. PyTorch Lightning/5. Create the policy.mp4
18.9 MB
~Get Your Files Here !/10. Prioritized Experience Replay/8. Check the resulting agent.mp4
17.6 MB
~Get Your Files Here !/5. Refresher Deep Q-Learning/4. Target Network.mp4
17.4 MB
~Get Your Files Here !/5. Refresher Deep Q-Learning/2. Deep Q-Learning.mp4
17.0 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/7. Discount factor.mp4
15.5 MB
~Get Your Files Here !/3. Refresher Q-Learning/3. Solving control tasks with temporal difference method.mp4
15.2 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/11. Solving a Markov decision process.mp4
14.8 MB
~Get Your Files Here !/8. Double Deep Q-Learning/1. Maximization bias and Double Deep Q-Learning.mp4
14.5 MB
~Get Your Files Here !/3. Refresher Q-Learning/2. Temporal difference methods.mp4
13.2 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/10. Bellman equations.mp4
13.0 MB
~Get Your Files Here !/3. Refresher Q-Learning/4. Q-Learning.mp4
11.6 MB
~Get Your Files Here !/8. Double Deep Q-Learning/4. Check the resulting agent.mp4
9.6 MB
~Get Your Files Here !/5. Refresher Deep Q-Learning/3. Experience replay.mp4
9.4 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/4. Types of Markov decision process.mp4
9.1 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/8. Policy.mp4
7.8 MB
~Get Your Files Here !/1. Introduction/3. Google Colab.mp4
6.1 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/6. Reward vs Return.mp4
5.6 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/5. Trajectory vs episode.mp4
5.2 MB
~Get Your Files Here !/1. Introduction/4. Where to begin.mp4
4.8 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/9. State values v(s) and action values q(s,a).mp4
4.5 MB
~Get Your Files Here !/3. Refresher Q-Learning/5. Advantages of temporal difference methods.mp4
3.9 MB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/1. Module overview.mp4
2.7 MB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/1. Module overview.mp4
1.9 MB
~Get Your Files Here !/3. Refresher Q-Learning/1. Module overview.mp4
1.6 MB
~Get Your Files Here !/5. Refresher Deep Q-Learning/1. Module overview.mp4
1.3 MB
~Get Your Files Here !/1. Introduction/1. Introduction.mp4.jpg
179.0 kB
~Get Your Files Here !/10. Prioritized Experience Replay/3. DQN for visual inputs.srt
15.5 kB
~Get Your Files Here !/10. Prioritized Experience Replay/4. Prioritized Experience Repay Buffer.srt
15.4 kB
~Get Your Files Here !/10. Prioritized Experience Replay/5. Create the environment.srt
14.3 kB
~Get Your Files Here !/6. PyTorch Lightning/8. Define the class for the Deep Q-Learning algorithm.srt
14.0 kB
~Get Your Files Here !/10. Prioritized Experience Replay/6. Implement the Deep Q-Learning algorithm with Prioritized Experience Replay.srt
13.2 kB
~Get Your Files Here !/9. Dueling Deep Q-Networks/3. Create the dueling DQN.srt
11.9 kB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/1. Hyperparameter tuning with Optuna.srt
11.2 kB
~Get Your Files Here !/6. PyTorch Lightning/11. Define the train_step() method.srt
11.1 kB
~Get Your Files Here !/6. PyTorch Lightning/1. PyTorch Lightning.srt
10.7 kB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/2. Function approximators.srt
10.0 kB
~Get Your Files Here !/9. Dueling Deep Q-Networks/4. Create the environment - Part 1.srt
9.2 kB
~Get Your Files Here !/6. PyTorch Lightning/7. Create the environment.srt
9.1 kB
~Get Your Files Here !/8. Double Deep Q-Learning/3. Create the Double Deep Q-Learning algorithm.srt
8.7 kB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/5. How to represent a Neural Network.srt
8.4 kB
~Get Your Files Here !/6. PyTorch Lightning/13. Train the Deep Q-Learning algorithm.srt
7.7 kB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/6. Stochastic Gradient Descent.srt
7.4 kB
~Get Your Files Here !/6. PyTorch Lightning/3. Introduction to PyTorch Lightning.srt
7.1 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/2. Elements common to all control tasks.srt
7.0 kB
~Get Your Files Here !/9. Dueling Deep Q-Networks/6. Implement Deep Q-Learning.srt
6.8 kB
~Get Your Files Here !/9. Dueling Deep Q-Networks/5. Create the environment - Part 2.srt
6.8 kB
~Get Your Files Here !/6. PyTorch Lightning/6. Create the replay buffer.srt
6.7 kB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/4. Artificial Neurons.srt
6.7 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/3. The Markov decision process (MDP).srt
6.5 kB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/4. Define the objective function.srt
6.3 kB
~Get Your Files Here !/6. PyTorch Lightning/4. Create the Deep Q-Network.srt
6.1 kB
~Get Your Files Here !/10. Prioritized Experience Replay/7. Launch the training process.srt
5.9 kB
~Get Your Files Here !/6. PyTorch Lightning/5. Create the policy.srt
5.9 kB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/3. Log average return.srt
5.7 kB
~Get Your Files Here !/6. PyTorch Lightning/9. Define the play_episode() function.srt
5.6 kB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/7. Neural Network optimization.srt
5.1 kB
~Get Your Files Here !/6. PyTorch Lightning/10. Prepare the data loader and the optimizer.srt
5.0 kB
~Get Your Files Here !/6. PyTorch Lightning/12. Define the train_epoch_end() method.srt
4.8 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/7. Discount factor.srt
4.7 kB
~Get Your Files Here !/5. Refresher Deep Q-Learning/4. Target Network.srt
4.7 kB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/3. Artificial Neural Networks.srt
4.5 kB
~Get Your Files Here !/3. Refresher Q-Learning/2. Temporal difference methods.srt
4.2 kB
~Get Your Files Here !/3. Refresher Q-Learning/3. Solving control tasks with temporal difference method.srt
4.2 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/11. Solving a Markov decision process.srt
3.7 kB
~Get Your Files Here !/6. PyTorch Lightning/14. Explore the resulting agent.srt
3.7 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/10. Bellman equations.srt
3.5 kB
~Get Your Files Here !/5. Refresher Deep Q-Learning/2. Deep Q-Learning.srt
3.4 kB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/5. Create and launch the hyperparameter tuning job.srt
3.3 kB
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/6. Explore the best trial.srt
3.1 kB
~Get Your Files Here !/3. Refresher Q-Learning/4. Q-Learning.srt
2.9 kB
~Get Your Files Here !/9. Dueling Deep Q-Networks/7. Check the resulting agent.srt
2.8 kB
~Get Your Files Here !/5. Refresher Deep Q-Learning/3. Experience replay.srt
2.6 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/4. Types of Markov decision process.srt
2.5 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/8. Policy.srt
2.4 kB
~Get Your Files Here !/1. Introduction/4. Where to begin.srt
2.1 kB
~Get Your Files Here !/1. Introduction/3. Google Colab.srt
2.0 kB
~Get Your Files Here !/10. Prioritized Experience Replay/8. Check the resulting agent.srt
2.0 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/6. Reward vs Return.srt
1.9 kB
~Get Your Files Here !/8. Double Deep Q-Learning/4. Check the resulting agent.srt
1.8 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/9. State values v(s) and action values q(s,a).srt
1.3 kB
~Get Your Files Here !/3. Refresher Q-Learning/5. Advantages of temporal difference methods.srt
1.3 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/5. Trajectory vs episode.srt
1.3 kB
~Get Your Files Here !/2. Refresher The Markov Decision Process (MDP)/1. Module overview.srt
1.2 kB
~Get Your Files Here !/4. Refresher Brief introduction to Neural Networks/1. Module overview.srt
850 Bytes
~Get Your Files Here !/3. Refresher Q-Learning/1. Module overview.srt
798 Bytes
~Get Your Files Here !/5. Refresher Deep Q-Learning/1. Module overview.srt
602 Bytes
~Get Your Files Here !/Bonus Resources.txt
386 Bytes
~Get Your Files Here !/1. Introduction/2. Reinforcement Learning series.html
377 Bytes
Get Bonus Downloads Here.url
182 Bytes
~Get Your Files Here !/6. PyTorch Lightning/2.1 Google colab.html
176 Bytes
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/2.1 Google colab.html
176 Bytes
~Get Your Files Here !/6. PyTorch Lightning/2. Link to the code notebook.html
169 Bytes
~Get Your Files Here !/7. Hyperparameter tuning with Optuna/2. Link to the code notebook.html
169 Bytes
~Get Your Files Here !/8. Double Deep Q-Learning/2. Link to the code notebook.html
169 Bytes
~Get Your Files Here !/9. Dueling Deep Q-Networks/2.1 Google colab.html
166 Bytes
~Get Your Files Here !/8. Double Deep Q-Learning/2.1 Google colab.html
165 Bytes
~Get Your Files Here !/9. Dueling Deep Q-Networks/2. Link to the code notebook.html
159 Bytes
~Get Your Files Here !/1. Introduction/1.1 Advanced Reinforcement Learning in Python from DQN to SAC.html
147 Bytes
~Get Your Files Here !/1. Introduction/1.2 Reinforcement Learning beginner to master.html
145 Bytes
~Get Your Files Here !/10. Prioritized Experience Replay/1. Prioritized Experience Replay.html
79 Bytes
~Get Your Files Here !/10. Prioritized Experience Replay/2. Link to the code notebook.html
79 Bytes
~Get Your Files Here !/11. Noisy Deep Q-Networks/1. Noisy Deep Q-Networks.html
79 Bytes
~Get Your Files Here !/12. N-step Deep Q-Learning/1. N-step Deep Q-Learning.html
79 Bytes
~Get Your Files Here !/13. Distributional Deep Q-Networks/1. Distributional Deep Q-Networks.html
79 Bytes
~Get Your Files Here !/9. Dueling Deep Q-Networks/1. Dueling Deep Q-Networks.html
79 Bytes
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