Modern Reinforcement Learning- Deep Q Learning in PyTorch

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Modern Reinforcement Learning- Deep Q Learning in PyTorch

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收录时间：2021-04-10
最近下载：2024-11-08

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文件列表

  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/018 Analyzing the Paper.mp4 292.7 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/05 Deep Reinforcement Learning with Double Q Learning/031 Analyzing the Paper.mp4 191.5 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/07 Improving On Our Solutions/038 Consolidating Our Code Base for Maximum Extensability.mp4 176.9 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/033 Analyzing the Paper.mp4 140.5 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/009 Temporal Difference Learning.mp4 135.8 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/010 Dealing with Continuous State Spaces with Deep Neural Networks.mp4 110.4 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/003 How to Succeed in this Course.mp4 110.3 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/019 How to Modify the OpenAI Gym Atari Environments.mp4 85.8 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/030 Coding the Deep Q Agent Step 5 - The Main Loop and Analyzing the Performance.mp4 76.5 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/035 Coding the Dueling Deep Q Learning Agent and Analyzing Performance.mp4 74.0 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/025 How to Code the Deep Q Network.mp4 69.7 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/024 How to Code the Agents Memory.mp4 64.4 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/005 Markov Decision Processes.mp4 63.4 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/012 Naive Deep Q Learning in Code Step 2 - Coding the Agent Class.mp4 63.1 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/05 Deep Reinforcement Learning with Double Q Learning/032 Coding the Double Q Learning Agent and Analyzing Performance.mp4 61.1 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/004 Agents Environments and Actions.mp4 60.6 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/07 Improving On Our Solutions/037 Implementing a Command Line Interface for Rapid Model Testing.mp4 59.9 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/017 How to Read Deep Learning Papers.mp4 52.1 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/006 Value Functions Action Value Functions and the Bellman Equation.mp4 49.5 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/013 Naive Deep Q Learning in Code Step 3 - Coding the Main Loop and Learning.mp4 48.0 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/011 Naive Deep Q Learning in Code Step 1 - Coding the Deep Q Network.mp4 46.3 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/026 Coding the Deep Q Agent Step 1 - Coding the Constructor.mp4 41.7 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/029 Coding the Deep Q Agent Step 4 - The Agents Learn Function.mp4 39.8 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/008 The Explore-Exploit Dilemma.mp4 39.7 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/036 Coding the Dueling Double Deep Q Learning Agent and Analyzing Performance.mp4 39.1 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/08 Conclusion/039 Summarizing What Weve Learned.mp4 37.2 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/028 Coding the Deep Q Agent Step 3 - Memory Model Saving and Network Copying.mp4 32.6 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/023 How to Add Reward Clipping Fire First and No Ops.mp4 32.1 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/001 What You Will Learn In This Course.mp4 30.4 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/007 Model Free vs. Model Based Learning.mp4 26.5 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/021 How to Stack the Preprocessed Atari Screen Images.mp4 25.7 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/002 Required Background software and hardware.mp4 24.8 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/034 Coding the Dueling Deep Q Network.mp4 24.7 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/016 Dealing with Screen Images with Convolutional Neural Networks.mp4 20.7 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/015 Naive Deep Q Learning in Code Step 5 - Analyzing Our Agents Performance.mp4 19.8 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/014 Naive Deep Q Learning in Code Step 4 - Verifying the Functionality of Our Code.mp4 19.6 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/020 How to Preprocess the OpenAI Gym Atari Screen Images.mp4 19.5 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/027 Coding the Deep Q Agent Step 2 - Epsilon-Greedy Action Selection.mp4 16.0 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/022 How to Combine All the Changes.mp4 9.7 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/09 Bonus Lecture/040 Bonus Video Where to Go From Here.mp4 6.2 MB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/018 Analyzing the Paper.en.srt 32.4 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/010 Dealing with Continuous State Spaces with Deep Neural Networks.en.srt 24.9 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/05 Deep Reinforcement Learning with Double Q Learning/031 Analyzing the Paper.en.srt 24.2 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/009 Temporal Difference Learning.en.srt 24.0 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/033 Analyzing the Paper.en.srt 21.3 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/07 Improving On Our Solutions/038 Consolidating Our Code Base for Maximum Extensability.en.srt 20.1 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/019 How to Modify the OpenAI Gym Atari Environments.en.srt 19.4 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/005 Markov Decision Processes.en.srt 16.6 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/030 Coding the Deep Q Agent Step 5 - The Main Loop and Analyzing the Performance.en.srt 14.9 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/07 Improving On Our Solutions/037 Implementing a Command Line Interface for Rapid Model Testing.en.srt 14.8 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/004 Agents Environments and Actions.en.srt 13.8 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/035 Coding the Dueling Deep Q Learning Agent and Analyzing Performance.en.srt 13.3 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/024 How to Code the Agents Memory.en.srt 12.5 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/006 Value Functions Action Value Functions and the Bellman Equation.en.srt 12.5 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/017 How to Read Deep Learning Papers.en.srt 11.8 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/025 How to Code the Deep Q Network.en.srt 11.7 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/05 Deep Reinforcement Learning with Double Q Learning/032 Coding the Double Q Learning Agent and Analyzing Performance.en.srt 9.9 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/029 Coding the Deep Q Agent Step 4 - The Agents Learn Function.en.srt 9.7 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/012 Naive Deep Q Learning in Code Step 2 - Coding the Agent Class.en.srt 9.4 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/011 Naive Deep Q Learning in Code Step 1 - Coding the Deep Q Network.en.srt 8.9 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/003 How to Succeed in this Course.en.srt 8.4 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/008 The Explore-Exploit Dilemma.en.srt 8.2 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/026 Coding the Deep Q Agent Step 1 - Coding the Constructor.en.srt 7.5 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/08 Conclusion/039 Summarizing What Weve Learned.en.srt 7.5 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/001 What You Will Learn In This Course.en.srt 7.3 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/036 Coding the Dueling Double Deep Q Learning Agent and Analyzing Performance.en.srt 7.1 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/013 Naive Deep Q Learning in Code Step 3 - Coding the Main Loop and Learning.en.srt 6.4 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/016 Dealing with Screen Images with Convolutional Neural Networks.en.srt 6.0 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/002 Required Background software and hardware.en.srt 5.8 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/007 Model Free vs. Model Based Learning.en.srt 5.5 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/023 How to Add Reward Clipping Fire First and No Ops.en.srt 4.9 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/034 Coding the Dueling Deep Q Network.en.srt 4.8 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/015 Naive Deep Q Learning in Code Step 5 - Analyzing Our Agents Performance.en.srt 4.5 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/028 Coding the Deep Q Agent Step 3 - Memory Model Saving and Network Copying.en.srt 3.0 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/027 Coding the Deep Q Agent Step 2 - Epsilon-Greedy Action Selection.en.srt 2.3 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/021 How to Stack the Preprocessed Atari Screen Images.en.srt 2.2 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/09 Bonus Lecture/040 Bonus Video Where to Go From Here.en.srt 1.9 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/014 Naive Deep Q Learning in Code Step 4 - Verifying the Functionality of Our Code.en.srt 1.7 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/020 How to Preprocess the OpenAI Gym Atari Screen Images.en.srt 1.7 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/022 How to Combine All the Changes.en.srt 1.4 kB
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/ReadMe.txt 220 Bytes
  • ReadMe.txt 220 Bytes
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/external-assets-links.txt 165 Bytes
  • Visit Coursedrive.org.url 124 Bytes
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/Visit Coursedrive.org.url 124 Bytes
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/external-assets-links.txt 110 Bytes
  • Modern Reinforcement Learning- Deep Q Learning in PyTorch/05 Deep Reinforcement Learning with Double Q Learning/external-assets-links.txt 89 Bytes

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