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80 lines
4.5 KiB
Markdown
80 lines
4.5 KiB
Markdown
# The Hugging Face Deep Reinforcement Learning Class 🤗
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In this free course, you will:
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- 📖 Study Deep Reinforcement Learning in **theory and practice**.
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- 🧑💻 Learn to **use famous Deep RL libraries** such as Stable Baselines3, RL Baselines3 Zoo, and RLlib.
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- 🤖 Train agents in **unique environments** such as SnowballFight, Huggy the Doggo 🐶, and classical ones such as Space Invaders and PyBullet.
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- 💾 **Publish your trained agents in one line of code to the Hugging Face Hub**. But also **download powerful agents from the community**.
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- 🏆 **Participate in challenges** where you will evaluate your agents against other teams.
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- 🖌️🎨 **Learn to share your own environments made with Unity and Godot**.
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➡️➡️➡️ Don't forget to sign up here: https://forms.gle/4bbgzs3oVZMjgDed7
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The best way to keep in touch is to **join our discord server to exchange with the community and with us** 👉🏻 https://discord.gg/aYka4Yhff9
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And don't forget to share with your friends who want to learn 🤗!
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## The Syllabus 🏗️
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| 📆 Publishing date | 📘 Unit | 👩💻 Hands-on |
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|---------------|----------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
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| May, the 4th | An Introduction to Deep Reinforcement Learning | Train a Deep Reinforcement Learning lander agent to land correctly on the Moon 🌕 using Stable-Baselines3 |
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| May, the 11th | Bonus | 🎁 it's a surprise 🎁 |
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| May, the 18th | Q-Learning | Train an agent to cross a Frozen lake in this new version of the environment. |
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| June, the 1st | Deep Q-Learning and improvements | Train a Deep Q-Learning agent to play Space Invaders |
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| | Policy-based methods | 🏗️ |
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| | Actor-Critic Methods | 🏗️ |
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| | Proximal Policy Optimization (PPO) | 🏗️ |
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| | Decision Transformers and offline Reinforcement Learning | 🏗️ |
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| | Towards better explorations methods | 🏗️ |
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## The library you'll learn during this course
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- [Stable-Baselines3](https://github.com/DLR-RM/stable-baselines3)
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- [RL Baselines3 Zoo](https://github.com/DLR-RM/rl-baselines3-zoo)
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- [RLlib](https://docs.ray.io/en/latest/rllib/index.html)
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- [CleanRL](https://github.com/vwxyzjn/cleanrl)
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- More to come 🏗️
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## The Environments you'll use
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### Custom environments made by the Hugging Face Team using Unity and Godot
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- Huggy the Doggo 🐶
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(Based on [Unity's Puppo the Corgi work](https://blog.unity.com/technology/puppo-the-corgi-cuteness-overload-with-the-unity-ml-agents-toolkit))
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- SnowballFight ☃️
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👉 Play it here: https://huggingface.co/spaces/ThomasSimonini/SnowballFight
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- More to come 🚧
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### Gym classic controls environments 🕹️
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- Lunar-Lander v2 🚀🌙
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### PyBullet 🤖
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- More to come 🚧
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### Gym Atari environments 👾
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- Space Invaders 👾
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### MLAgents environments 🖌️
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- More to come 🚧
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## Prerequisites
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- Good skills in Python 🐍
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- Basics in Deep Learning and Pytorch
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If it's not the case yet, you can check these free resources:
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- Python: https://www.udacity.com/course/introduction-to-python--ud1110
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- Intro to Deep Learning with PyTorch: https://www.udacity.com/course/deep-learning-pytorch--ud188
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- PyTorch in 60min: https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html
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