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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Free course that takes you from zero to Reinforcement Learning PRO π¦Έπ»βπ¦Έπ½
| Date | Stars |
|---|---|
| 2026-07-24 | 1564 |
| 2026-07-25 | 1564 |
| 2026-07-28 | 1566 |
| 2026-07-30 | 1566 |
| 2026-07-31 | 1566 |
| 2026-08-06 | 1566 |
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<div align="center"> <h1>The Hands-on Reinforcement Learning course π </h1> <h2>From zero to HERO π¦Έπ»βπ¦Έπ½</h2> <h3><i>Out of intense complexities, intense simplicities emerge.</i></h3> <h4>-- Winston Churchill</h4> </div>  [](https://twitter.com/paulabartabajo_) ## Contents * [Welcome to the course](#welcome-to-the-course-) * [Lectures](#lectures) * [Wanna contribute?](#wanna-contribute) * [Let's connect!](#lets-connect) ## Welcome to the course π€β€οΈ Welcome to my step by step hands-on-course that will take you from basic reinforcement learning to cutting-edge deep RL. We will start with a short intro of what RL is, what is it used for, and how does the landscape of current RL algorithms look like. Then, in each following chapter we will solve a different problem, with increasing difficulty: - π easy - ππ medium - πππ hard Ultimately, the most complex RL problems involve a mixture of reinforcement learning algorithms, optimizations and Deep Learning techniques. You do not need to know deep learning (DL) to follow along this course. I will give you enough context to get you familiar with DL philosophy and understand how it becomes a crucial ingredient in modern reinforcement learning. ## Lectures 0. [Introduction to Reinforcement Learning](https://datamachines.xyz/2021/11/17/hands-on-reinforcement-learning-course-part-1/) 1. [Q-learning to drive a taxi π](01_taxi/README.md) 2. [SARSA to beat gravity π](02_mountain_car/README.md) 3. [Parametric Q learning to keep the balance π π](03_cart_pole/README.md) 4. [Policy gradients to land on the Moon π](04_lunar_lander/README.md) ## Wanna contribute? There are 2 things you can do to contribute to this course: 1. Spread the word and share it on [Twitter](https://ctt.ac/Aa7dt), [LinkedIn](https://www.linkedin.com/shareArticle?mini=true&url=http%3A//datamachines.xyz/the-hands-on-reinforcement-learning-course-page/&title=The%20hands-on%20Reinforcement%20Learning%20course&summary=Wanna%20learn%20Reinforcement%20Learning?%20%F0%9F%A4%94%0A%40paulabartabajo%20has%20a%20course%20on%20%23reinforcementlearning,%20that%20takes%20you%20from%20zero%20to%20PRO%20%F0%9F%A6%B8%F0%9F%8F%BB%E2%80%8D%F0%9F%A6%B8%F0%9F%8F%BD.%0A%0A%F0%9F%91%89%F0%9F%8F%BD%20With%20lots%20of%20Python%0A%F0%9F%91%89%F0%9F%8F%BD%20Intuitions,%20tips%20%26%20tricks%20explained.%0A%F0%9F%91%89%F0%9F%8F%BD%20And%20free,%20by%20the%20way.%0A%0AReady%20to%20start?%20Click%20%F0%9F%91%87%F0%9F%8F%BD%F0%9F%91%87%F0%9F%8F%BE%F0%9F%91%87%F0%9F%8F%BF%0A%0A%23MachineLearning&source=) 2. Open a [pull request](https://github.com/Paulescu/hands-on-rl/pulls) to fix a bug or improve the code readability. ### Thanks β€οΈ Special thanks to all the students who contributed with valuable feedback and pull requests β€ - [Neria Uzan](https://www.linkedin.com/in/neria-uzan-369803107/) - [Anthony Lapadula](https://www.linkedin.com/in/anthony-lapadula-9343a5b/) - [Petar SekuliΔ](https://www.linkedin.com/in/petar-sekulic-ml/) ## Let's connect! ππ½ Subscribe for **FREE** to the [Real-World ML newsletter](https://realworldml.net/subscribe/) π§ ππ½ Follow me on [Twitter](https://twitter.com/paulabartabajo_) and [LinkedIn](https://www.linkedin.com/in/pau-labarta-bajo-4432074b/) π‘
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Would you bet a product on this? Bounded 0β100 and slow moving.
matched fp:2102d67e45d4497e, topic:reinforcement-learning, topic:deep-reinforcement-learning, desc:reinforcement learning