mingzhehu-duke/hands-on-rl

Free course that takes you from zero to Reinforcement Learning PRO 🦸🏻‍🦸🏽

The Hands-on Reinforcement Learning course 🚀

From zero to HERO 🦸🏻‍🦸🏽

Out of intense complexities, intense simplicities emerge

--Winston Churchill

Welcome ❤️

Welcome to my step by step hands-on-course that will take you from basic reinforcement learning to cutting-edge deep RL.

We will start with a short intro of what RL is, what is it used for, and how does the landscape of current RL algorithms look like.

Then, in each following chapter we will solve a different problem, with increasing difficulty:

• 🏆 easy
• 🏆🏆 medium
• 🏆🏆🏆 hard

Ultimately, the most complex RL problems involve a mixture of reinforcement learning algorithms, optimizations and Deep Learning techniques.

You do not need to know deep learning (DL) to follow along this course.

I will give you enough context to get you familiar with DL philosophy and understand how it becomes a crucial ingredient in modern reinforcement learning.

Lectures

0. Introduction to Reinforcement Learning
1. Q-learning to drive a taxi 🏆
2. SARSA to beat gravity 🏆
3. Parametric Q learning to keep the balance 💃 🏆

Thanks❤️

Special thanks to all the students who contributed with valuable feedback and pull requests.

• Neria Uzan
• Anthony Lapadula

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