⚠️ The new version of Deep Reinforcement Learning Course starts on October the 2nd 2020. ➡️ More info here ⬅️
Deep Reinforcement Learning Course is a free series of blog posts and videos 🆕 about Deep Reinforcement Learning, where we'll learn the main algorithms, and how to implement them with Tensorflow.
📜The articles explain the concept from the big picture to the mathematical details behind it. 📹 The videos explain how to create the agent with Tensorflow
📜 Part 1: Introduction to Reinforcement Learning ARTICLE
Part 2: Q-learning with FrozenLake
Part 3: Deep Q-learning with Doom
Part 4: Policy Gradients with Doom
Part 3+: Improvments in Deep Q-Learning
Part 5: Advantage Advantage Actor Critic (A2C)
Part 6: Proximal Policy Gradients
Part 7: Curiosity Driven Learning made easy Part I
Part 8: Random Network Distillation with PyTorch
👨💻 A trained RND agent that learned to play Montezuma's revenge (21 hours of training with a Tesla K80
Any questions 👨💻
If you have any questions, feel free to ask me:
🌐 : https://simoninithomas.github.io/deep-rl-course/
How to help 🙌
- Clap our articles and like our videos a lot:Clapping in Medium means that you really like our articles. And the more claps we have, the more our article is shared Liking our videos help them to be much more visible to the deep learning community.
- Share and speak about our articles and videos: By sharing our articles and videos you help us to spread the word.
- Improve our notebooks: if you found a bug or a better implementation you can send a pull request.