YoVDO

Q Learning Tutorial - Training Loop

Offered By: Edan Meyer via YouTube

Tags

PyTorch Courses Reinforcement Learning Courses Q-learning Courses

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

Computational Neuroscience
University of Washington via Coursera Reinforcement Learning
Brown University via Udacity Reinforcement Learning
Indian Institute of Technology Madras via Swayam FA17: Machine Learning
Georgia Institute of Technology via edX Introduction to Reinforcement Learning
Higher School of Economics via Coursera