Reinforcement learning course: hands-on, step by step, and free

Reinforcement Learning (RL) is the kind of machine learning closest to how humans and animals learn. It offers us a path towards building general AI systems that can tackle the most complex problems we can think of. In this reinforcement learning course, I will teach you how.

Welcome to the Hands-on reinforcement learning course ❤️

Let’s walk this beautiful path from the fundamentals to cutting edge deep reinforcement learning, together!

👉🏽From zero to HERO 🦸🏻🦸🏼🦸🏽🦸🏾🦸🏿🦸‍♂️🦸‍♀️

👉🏽Step by step

👉🏽Clean Python code

👉🏽Intuitions, tips and tricks explained.


All the reinforcement learning course code is in this Github repo. Don’t forget to give it a ⭐!


reinforcement learning course

1. Introduction to Reinforcement Learning

This first part covers the bare minimum concept and theory you need to embark on this journey, with practical examples and the first code snippet!

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reinforcement learning course

2. Q learning to drive a taxi

Q learning is a classical RL algorithm published in the 90s. In this first lesson, we use tabular Q-learning to train a smart taxi driver. Ready to drive?

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3. SARSA to beat gravity

The Mountain Car problem is an environment where gravity exists (what a surprise) and the goal is to help a poor car win the battle against it.

SARSA is a classical online algorithm that solve this problem like a charm.

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parametric q learning

4. Parametric Q learning to keep the balance (1/3)

Parametric Q learning combines the strengths of classical Q-learning with modern optimization techniques from Supervised Machine Learning.

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deep q learning

5. Deep Q learning to keep the balance (2/3)

Let’s replace the linear model from the previous lesson with a deep neural network. And kick-ass solve the Cart Pole environment.

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6. Hyperparameters In Deep RL

Hyperparameters in Deep RL are critical to training successful agents. In today’s lesson, we will learn how to find the ones that make you a happy Deep RL developer.

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Deep Learning: Faster, Better, And Free In 3 Easy Steps

Tired of training deep learning models on your laptop, at the speed of… a turtle? 🐢 Not enthusiastic about buying an expensive GPU or optimizing cloud services bills? 💸 Wish there was a better way to do it?

Luckily for you, the answer to the last question is yes. 

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7. Policy Gradients to get to the Moon

Policy gradients are a family of powerful reinforcement learning algorithms that can solve complex control tasks. In today’s lesson, we will implement vanilla policy gradients from scratch and land on the Moon 🌗.

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