GitHub - alessiodm/drl-zh: Deep Reinforcement Learning: Zero to Hero!
source link: https://github.com/alessiodm/drl-zh
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Deep Reinforcement Learning: Zero to Hero!
Welcome to the most hands-on reinforcement learning experience!
This is a short and practical introductory course on foundational and classic deep reinforcement learning algorithms. By the end of the course, you will have written from scratch algorithms like DQN, SAC, PPO, as well as understood at a high-level the theory behind them.
We will be able to train an AI to play Atari games and land on the Moon!
Environment Setup
To make sure we can focus on learning, the environment setup is opinionated 😊 Here it is:
-
Install Miniconda
Why conda? Because it's a full envinronment manager, and we can choose the Python version too.
-
Checkout this Git repository, and
cd
into its folder. -
Create and activate the
drlzh
virtual environment:conda create --name drlzh python=3.11 conda activate drlzh
-
Install Poetry and install dependencies:
Dependencies include
gymnasium[accept-rom-license]
for Atari. Make sure to accept the license agreement when installing the dependencies of the project via Poetry.pip install poetry poetry install
-
Install Visual Studio Code
How Do I Start?
Open this repository folder in Visual Studio Code (make sure to keep the .vscode
folder for
settings consistency, running on Jupyter might require some tweaks to code and imports).
Open the first 00_Intro.ipynb
notebook in Visual Studio Code, and follow along! From there, just
keep moving on to the next notebooks. If you get stuck, feel free to check the /solution
folder.
For an expanded treatment and step-by-step coding, check out the YouTube videos!
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