Modern Reinforcement Learning Deep Q Learning in PyTorch
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Torrent Size : | 2.36 GB |
Modern Reinforcement Learning Deep Q Learning in PyTorch
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Torrent File Content (87 files)
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 -
04 Human Level Control Through Deep Reinforcement Learning From Paper to Code
018 Analyzing the Paper.mp4 -
279.17 MB
Visit Coursedrive.org.url -
124 bytes
ReadMe.txt -
220 bytes
Visit Coursedrive.org.url -
124 bytes
01 Introduction
001 What You Will Learn In This Course.en.srt -
001 What You Will Learn In This Course.en.srt -
7.12 KB
001 What You Will Learn In This Course.mp4 -
29.02 MB
002 Required Background software and hardware.en.srt -
5.69 KB
002 Required Background software and hardware.mp4 -
23.68 MB
003 How to Succeed in this Course.en.srt -
8.24 KB
003 How to Succeed in this Course.mp4 -
105.19 MB
02 Fundamentals of Reinforcement Learning
004 Agents Environments and Actions.en.srt -
004 Agents Environments and Actions.en.srt -
13.48 KB
004 Agents Environments and Actions.mp4 -
57.77 MB
005 Markov Decision Processes.en.srt -
16.2 KB
005 Markov Decision Processes.mp4 -
60.48 MB
006 Value Functions Action Value Functions and the Bellman Equation.en.srt -
12.16 KB
006 Value Functions Action Value Functions and the Bellman Equation.mp4 -
47.17 MB
007 Model Free vs. Model Based Learning.en.srt -
5.34 KB
007 Model Free vs. Model Based Learning.mp4 -
25.29 MB
008 The Explore-Exploit Dilemma.en.srt -
8.04 KB
008 The Explore-Exploit Dilemma.mp4 -
37.87 MB
009 Temporal Difference Learning.en.srt -
23.4 KB
009 Temporal Difference Learning.mp4 -
129.49 MB
03 Deep Learning Crash Course
010 Dealing with Continuous State Spaces with Deep Neural Networks.en.srt -
010 Dealing with Continuous State Spaces with Deep Neural Networks.en.srt -
24.28 KB
010 Dealing with Continuous State Spaces with Deep Neural Networks.mp4 -
105.27 MB
011 Naive Deep Q Learning in Code Step 1 - Coding the Deep Q Network.en.srt -
8.66 KB
011 Naive Deep Q Learning in Code Step 1 - Coding the Deep Q Network.mp4 -
44.16 MB
012 Naive Deep Q Learning in Code Step 2 - Coding the Agent Class.en.srt -
9.22 KB
012 Naive Deep Q Learning in Code Step 2 - Coding the Agent Class.mp4 -
60.14 MB
013 Naive Deep Q Learning in Code Step 3 - Coding the Main Loop and Learning.en.srt -
6.26 KB
013 Naive Deep Q Learning in Code Step 3 - Coding the Main Loop and Learning.mp4 -
45.75 MB
014 Naive Deep Q Learning in Code Step 4 - Verifying the Functionality of Our Code.en.srt -
1.7 KB
014 Naive Deep Q Learning in Code Step 4 - Verifying the Functionality of Our Code.mp4 -
18.73 MB
015 Naive Deep Q Learning in Code Step 5 - Analyzing Our Agents Performance.en.srt -
4.37 KB
015 Naive Deep Q Learning in Code Step 5 - Analyzing Our Agents Performance.mp4 -
18.92 MB
016 Dealing with Screen Images with Convolutional Neural Networks.en.srt -
5.87 KB
016 Dealing with Screen Images with Convolutional Neural Networks.mp4 -
19.76 MB
04 Human Level Control Through Deep Reinforcement Learning From Paper to Code
017 How to Read Deep Learning Papers.en.srt -
017 How to Read Deep Learning Papers.en.srt -
11.54 KB
017 How to Read Deep Learning Papers.mp4 -
49.72 MB
018 Analyzing the Paper.en.srt -
31.69 KB
ReadMe.txt -
220 bytes
019 How to Modify the OpenAI Gym Atari Environments.en.srt -
18.92 KB
019 How to Modify the OpenAI Gym Atari Environments.mp4 -
81.79 MB
020 How to Preprocess the OpenAI Gym Atari Screen Images.en.srt -
1.68 KB
020 How to Preprocess the OpenAI Gym Atari Screen Images.mp4 -
18.55 MB
021 How to Stack the Preprocessed Atari Screen Images.en.srt -
2.14 KB
021 How to Stack the Preprocessed Atari Screen Images.mp4 -
24.53 MB
022 How to Combine All the Changes.en.srt -
1.41 KB
022 How to Combine All the Changes.mp4 -
9.23 MB
023 How to Add Reward Clipping Fire First and No Ops.en.srt -
4.81 KB
023 How to Add Reward Clipping Fire First and No Ops.mp4 -
30.62 MB
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