Reinforcement Learning for Gaming Full Python Course in 9 Hours

Learners: 40,203

Instructor: Nicholas Renotte

Duration:

This 9-hour course is the perfect way to learn how to apply machine learning to gaming. It covers reinforcement learning tutorials for gaming using Python and Stable Baselines 3. You'll learn best practices for training reinforcement learning models for games, as well as how to preprocess environments, build RL models, run them live, and more. Plus, you'll get to practice on Mario, Doom, and Streetfighter. Connect with the instructor, Nick, on LinkedIn, Facebook, GitHub, and Patreon for support and discussion. Get ready to take your gaming to the next level with this comprehensive course! ▼▲

Course Feature Course Overview Course Provider Discussion and Reviews

Go to class

Course Feature

Cost:

Free

Provider:

Youtube

Certificate:

No Information

Language:

English

Start Date:

2022-07-07 00:00:00

Course Overview

❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 21st, 2023]

This 9-hour course provides an in-depth overview of Reinforcement Learning (RL) for gaming using Python and Stable Baselines 3. It covers best practices for training RL models for games, and includes tutorials for Mario, Doom, and Streetfighter. Participants will learn how to preprocess environments, build RL models, run the RL model live, train for other levels, and use curriculum learning and reward shaping. They will also learn how to install and setup dependencies, create a custom OpenAI Gym environment, train the RL model, and get the model to smash Chrome Dino. At the end of the course, participants will have a comprehensive understanding of RL for gaming.