DeepRL-Tutorials
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
Explore and understand deep reinforcement learning algorithms through easy-to-follow code examples and explanations.
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Free · no card · unsubscribe anytimeContains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
DeepRL-Tutorials has 1.1k stars on GitHub. It has been forked 325 times. DeepRL-Tutorials is written mainly in Jupyter Notebook. It has been in active development since 2018. Its main topics are a2c, actor-critic, advantage-actor-critic, categorical-dqn.
What is DeepRL-Tutorials?
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
Is DeepRL-Tutorials open source?
DeepRL-Tutorials is an open-source project.
Is DeepRL-Tutorials free?
Yes. DeepRL-Tutorials is free and open source — you can use, modify and self-host it.
What language is DeepRL-Tutorials written in?
DeepRL-Tutorials is written mainly in Jupyter Notebook.
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