Python Reinforcement Learning Tutorial for Beginners in 25 Minutes

Want to break into Reinforcement Learning with Python?

Just not too sure where or how to start?

Well in this video you’ll learn the basics of creating an OpenAI gym environment in Python and training a reinforcement learning algorithm to solve the Lunar Lander problem. You’ll be able to leverage the stable_baselines algorithms to quickly and effectively train a deep reinforcement learning model in Python, the same pattern can be used over and again to train and solve multiple reinforcement learning problems.

In this video, you'll learn :
1. Installing Stable Baselines for Reinforcement Learning with Python
2. Training a Reinforcement Learning model using the ACER Algorithm
3. Running and Evaluating a Stable Baselines RL Model on LunarLander-v2

Get the code: https://github.com/nicknochnack/StableBaselinesRL

Reinforcement Learning Crash Course: https://youtu.be/cO5g5qLrLSo

Chapters:
0:00 - Start
1:55 - Reinforcement Learning Flow
4:09 - Installing Python Dependencies
6:10 - Importing RL Dependencies including stable_baselines
9:11 - Testing the LunarLander-v2 Environment
11:47 - Training an ACER Reinforcement Learning Model
17:52 - Evaluating the Model
20:30 - Saving and Reloading RL Model Weights

Oh, and don't forget to connect with me!
LinkedIn: https://www.linkedin.com/in/nicholasrenotte
Facebook: https://www.facebook.com/nickrenotte/
GitHub: https://github.com/nicknochnack
Patreon: https://www.patreon.com/nicholasrenotte
Join the Discussion on Discord: https://discord.gg/mtTTwYkB29

Happy coding!
Nick

P.s. Let me know how you go and drop a comment if you need a hand!