Modern Reinforcement Learning- Deep Q Learning in PyTorch
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- 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 279.2 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/05 Deep Reinforcement Learning with Double Q Learning/031 Analyzing the Paper.mp4 182.7 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/07 Improving On Our Solutions/038 Consolidating Our Code Base for Maximum Extensability.mp4 168.8 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/033 Analyzing the Paper.mp4 134.0 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/009 Temporal Difference Learning.mp4 129.5 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 105.3 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/003 How to Succeed in this Course.mp4 105.2 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 81.8 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 73.0 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 70.6 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 66.4 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 61.4 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/005 Markov Decision Processes.mp4 60.5 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 60.1 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 58.3 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/004 Agents Environments and Actions.mp4 57.8 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 57.1 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 49.7 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 47.2 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 45.7 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 44.2 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 39.8 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 38.0 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/008 The Explore-Exploit Dilemma.mp4 37.9 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 37.3 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/08 Conclusion/039 Summarizing What Weve Learned.mp4 35.5 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 31.1 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 30.6 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/001 What You Will Learn In This Course.mp4 29.0 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/007 Model Free vs. Model Based Learning.mp4 25.3 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 24.5 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/002 Required Background software and hardware.mp4 23.7 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 23.6 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/03 Deep Learning Crash Course/016 Dealing with Screen Images with Convolutional Neural Networks.mp4 19.8 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 18.9 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 18.7 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 18.6 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 15.3 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 9.2 MB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/09 Bonus Lecture/040 Bonus Video Where to Go From Here.mp4 6.0 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 31.7 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 24.3 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/05 Deep Reinforcement Learning with Double Q Learning/031 Analyzing the Paper.en.srt 23.6 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/009 Temporal Difference Learning.en.srt 23.4 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/06 Dueling Network Architectures for Deep Reinforcement Learning/033 Analyzing the Paper.en.srt 20.8 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/07 Improving On Our Solutions/038 Consolidating Our Code Base for Maximum Extensability.en.srt 19.6 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 18.9 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/005 Markov Decision Processes.en.srt 16.2 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 14.5 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 14.4 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/004 Agents Environments and Actions.en.srt 13.5 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 13.0 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 12.2 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 12.2 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 11.5 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 11.4 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 9.6 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 9.4 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 9.2 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 8.7 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/003 How to Succeed in this Course.en.srt 8.2 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/008 The Explore-Exploit Dilemma.en.srt 8.0 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 7.3 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/08 Conclusion/039 Summarizing What Weve Learned.en.srt 7.3 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/001 What You Will Learn In This Course.en.srt 7.1 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 6.9 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 6.3 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 5.9 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/01 Introduction/002 Required Background software and hardware.en.srt 5.7 KB
- Modern Reinforcement Learning- Deep Q Learning in PyTorch/02 Fundamentals of Reinforcement Learning/007 Model Free vs. Model Based Learning.en.srt 5.3 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 4.8 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 4.7 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 4.4 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 2.9 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 2.1 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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