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种子名称： Modern Reinforcement Learning- Deep Q Learning in PyTorch
文件类型： 视频
文件数目： 40个文件
文件大小： 2.36 GB
收录时间： 2020-8-28 21:17
已经下载： 3次
资源热度： 153
最近下载： 2024-7-1 03:21

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Modern Reinforcement Learning- Deep Q Learning in PyTorch.torrent

Modern Reinforcement Learning- Deep Q Learning in PyTorch/04 Human Level Control Through Deep Reinforcement Learning From Paper to Code/018 Analyzing the Paper.mp4279.17MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/001 What You Will Learn In This Course.mp429.02MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/002 Required Background software and hardware.mp423.68MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/003 How to Succeed in this Course.mp4105.19MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/004 Agents Environments and Actions.mp457.77MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/005 Markov Decision Processes.mp460.48MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/006 Value Functions Action Value Functions and the Bellman Equation.mp447.17MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/007 Model Free vs. Model Based Learning.mp425.29MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/008 The Explore-Exploit Dilemma.mp437.87MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/009 Temporal Difference Learning.mp4129.49MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/010 Dealing with Continuous State Spaces with Deep Neural Networks.mp4105.27MB

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.mp444.16MB

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.mp460.14MB

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.mp445.75MB

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.mp418.73MB

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.mp418.92MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/016 Dealing with Screen Images with Convolutional Neural Networks.mp419.76MB

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.mp449.72MB

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.mp481.79MB

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.mp418.55MB

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.mp424.53MB

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.mp49.23MB

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.mp430.62MB

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.mp461.4MB

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.mp466.44MB

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.mp439.81MB

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.mp415.26MB

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.mp431.1MB

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.mp438MB

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.mp472.96MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/05 Deep Reinforcement Learning with Double Q Learning/031 Analyzing the Paper.mp4182.66MB

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.mp458.28MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/033 Analyzing the Paper.mp4133.99MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/034 Coding the Dueling Deep Q Network.mp423.55MB

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.mp470.57MB

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.mp437.26MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/07 Improving On Our Solutions/037 Implementing a Command Line Interface for Rapid Model Testing.mp457.15MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/07 Improving On Our Solutions/038 Consolidating Our Code Base for Maximum Extensability.mp4168.75MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/08 Conclusion/039 Summarizing What Weve Learned.mp435.46MB

Modern Reinforcement Learning- Deep Q Learning in PyTorch/09 Bonus Lecture/040 Bonus Video Where to Go From Here.mp45.95MB