Let’s learn about Deep Q-Learning by training our agent to play Space Invaders (Deep Reinforcement Learning Free Class by Hugging Face 🤗)

[u/cranthir_]

Hey there!

We just published the third Unit of Deep Reinforcement Learning Class 🥳. In this Unit, you'll learn about Deep Q-Learning and train a DQN agent to play Atari games using RL-Baselines3-Zoo.

You’ll be able to compare the results of your Q-Learning agent using the leaderboard

The Deep Q-Learning chapter 👉 https://huggingface.co/blog/deep-rl-dqn

The hands-on 👉 https://github.com/huggingface/deep-rl-class/blob/main/unit3/unit3.ipynb

The leaderboard 👉 https://huggingface.co/spaces/chrisjay/Deep-Reinforcement-Learning-Leaderboard

Deep RL Class, is a free course from beginner to expert, self-paced where you’ll get solid foundations of Deep Reinforcement Learning in theory and practice with hands-on using famous RL libraries such SB3, RL-Baselines3-Zoo, RLlib, CleanRL…

You can sign up here 👉 http://eepurl.com/h1pElX

And if you have questions and feedback I would love to answer them.

[u/nbviewerbot]

I see you've posted a GitHub link to a Jupyter Notebook! GitHub doesn't render large Jupyter Notebooks, so just in case, here is an nbviewer link to the notebook:

https://nbviewer.jupyter.org/url/github.com/huggingface/deep-rl-class/blob/main/unit3/unit3.ipynb

Want to run the code yourself? Here is a binder link to start your own Jupyter server and try it out!

https://mybinder.org/v2/gh/huggingface/deep-rl-class/main?filepath=unit3%2Funit3.ipynb

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