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
Deep Learning with Python and PyTorch.IBM via edX Introduction to Machine Learning
Duke University via Coursera How Google does Machine Learning em Português Brasileiro
Google Cloud via Coursera Intro to Deep Learning with PyTorch
Facebook via Udacity Secure and Private AI
Facebook via Udacity