Deep Q-Learning/Deep Q-Network (DQN) Explained | Python Pytorch Deep Reinforcement Learning

Title:
Deep Q-Learning/Deep Q-Network (DQN) Explained | Python Pytorch Deep Reinforcement Learning
Description:

This tutorial contains step by step explanation, code walkthru, and demo of how Deep Q-Learning (DQL) works. We'll use DQL to solve the very simple Gymnasium FrozenLake-v1 Reinforcement Learning environment. We'll cover the differences between Q-Learning vs DQL, the Epsilon-Greedy Policy, the Policy Deep Q-Network (DQN), the Target DQN, and Experience Replay. After this video, you will understand DQL.

Want more videos like this? Support me here: https://www.buymeacoffee.com/johnnycode
GitHub Repo: https://github.com/johnnycode8/gym_solutions

Part 2 - Add Convolution Layers to DQN: https://youtu.be/qKePPepISiA

Reinforcement Learning Playlist: https://www.youtube.com/playlist?list=PL58zEckBH8fCt_lYkmayZoR9XfDCW9hte

Resources mentioned in video:
How to Solve FrozenLake-v1 with Q-Learning: https://youtu.be/ZhoIgo3qqLU
Need help installing the Gymnasium library? https://youtu.be/gMgj4pSHLww
Solve Neural Network in Python and by hand: https://youtu.be/6kOvmZDEMdc

00:00 Video Content
01:09 Frozen Lake Environment
02:16 Why Reinforcement Learning?
03:12 Epsilon-Greedy Policy
03:55 Q-Table vs Deep Q-Network
06:51 Training the Q-Table
10:10 Training the Deep Q-Network
14:49 Experience Replay
16:03 Deep Q-Learning Code Walkthru
29:49 Run Training Code & Demo

more » « less
Video Language:
English
Duration:
34:05
http://www.youtube.com/watch?v=EUrWGTCGzlA
Format: Youtube
Primary
Original
Added Mar 3, 2025  by OEVIDEOS
Format: Youtube
Primary
Original
This video is part of Amara Public.

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