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# deep-rl-bootcamp
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This repo will contain the syllabus of the Hugging Face Deep Reinforcement Learning Bootcamp.
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# The Hugging Face Deep Reinforcement Learning Bootcamp 🤗
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In this free bootcamp, 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 Hub**. But also **download powerful agents from the community**.
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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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# Unit 1: An Introduction to Deep Reinforcement Learning
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- Theory: An Introduction to Deep Reinforcement Learning
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- Hands-on: Train your first agent with SB3
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# Bonus: Train Huggy the Doggo
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# Unit 2: Q-Learning
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# Unit 3: Deep Q-Learning and improvements
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# Unit 4: Policy based methods
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# Unit 5: Actor Critic Methods
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# Unit 6: Proximal Policy Optimization (PPO)
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# Unit 7: Decision Transformers
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- Introduction to Deep Reinforcement Learning
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- Theory: C1 DRLC Introduction to Deep RL
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- Practice: Lunar Lander
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- Library: SB3
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- Bonus: Huggy
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- Value based methods: Q-Learning
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- Theory: Q-Learning
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- Practice: Frozen lake updated version
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- Deep Q-Learning and improvements
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- Theory: Deep Q-Learning and DDQN
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- Practice:
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