Q Learning Tutorial - Training Loop
Offered By: Edan Meyer via YouTube
Course Description
Overview
Dive into the training loop of Deep Q-Networks (DQN) in this 21-minute tutorial video, part 4 of a series on Q Learning. Explore the implementation details, including the policy, for loop, and reward mechanisms. Access the accompanying code on GitHub and refer to the original DQN paper for a deeper understanding. Ensure familiarity with previous videos in the series for a comprehensive grasp of Q Learning concepts.
Syllabus
Introduction
Training Leap
Policy
For Loop
Ord Reward
Append Reward
Taught by
Edan Meyer
Related Courses
Sample-based Learning MethodsUniversity of Alberta via Coursera Introduction to Reinforcement Learning in Python
Coursera Project Network via Coursera Artificial Intelligence for Business + ChatGPT Prize [2024]
Udemy Advanced AI: Deep Reinforcement Learning in Python
Udemy Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT
Udemy