Q-learning with numpy and OpenAI Taxi-v2 ???? (tutorial)

⚠️ We launched a new free Deep Reinforcement Learning Course with Hugging Face 🤗 from beginner to expert, here : huggingface.co/deep-rl-course/unit0/introduction
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We'll train an Q-learning agent with Numpy that learns to play Taxi-v2. Where he must take a passenger at one location and drop him off at another as fast as possible. 🚕

This video is part of the Deep Reinforcement Learning course with tensorflow 🕹️ 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 : simoninithomas.github.io/Deep_reinforcement_lea…

If you're new in Reinforcement Learning, please read first my article "An introduction to Reinforcement Learning": medium.freecodecamp.org/an-introduction-to-rein…

The Q-learning article: medium.freecodecamp.org/diving-deeper-into-rein…

The Q-learning notebook: github.com/simoninithomas/Deep_reinforcement_le…

This is my first video so if you have some feedbacks and advice please comment below.

Moreover if you have some questions you can ask me in the comments.

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