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I have been reading: Reinforcement Learning: An Introduction by Sutton and Barto. I admit it's a good read for learning RL whereas it's more theoretical with detailed algorithms.

Now, I want something more programming oriented resource(s) maybe a course, book, etc. I have been exploring Kaggle, Open-source RL projects.

I need this to learn and grasp a deeper understanding of RL from the perspective of a developer i.e optimized way of writing code, explanation about using the latest RL libraries, cloud services, etc.

nbro
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Arpit-Gole
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    Please, have a look at [this](https://ai.stackexchange.com/q/18798/2444), [this](https://ai.stackexchange.com/q/22010/2444) and [this question](https://ai.stackexchange.com/q/6997/2444). If any of those answers answer your question, let me know. – nbro Sep 05 '20 at 16:58
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    Thank you @nbro, I got what I needed. I see you are leading the AI SE community impressively. Keep up the good work. – Arpit-Gole Sep 06 '20 at 02:40
  • If you found what you were looking for and it's in the answers below, please, click on the "check" mark to accept the answer. If it's somewhere else (e.g. in the answer to another question), please, let us know. – nbro Sep 07 '20 at 13:46

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Arthur Juliani has some interesting Medium articles on reinforcement learning with TensorFlow backed up with code on GitHub.

  1. Part 0 — Q-Learning Agents
  2. Part 1 — Two-Armed Bandit
  3. Part 1.5 — Contextual Bandits
  4. Part 2 — Policy-Based Agents
  5. Part 3 — Model-Based RL
  6. Part 4 — Deep Q-Networks and Beyond
  7. Part 5 — Visualizing an Agent’s Thoughts and Actions
  8. Part 6 — Partial Observability and Deep Recurrent Q-Networks
  9. Part 7 — Action-Selection Strategies for Exploration
  10. Part 8 — Asynchronous Actor-Critic Agents (A3C)

As nbro pointed out Denny Britz has a good repository: https://github.com/dennybritz/reinforcement-learning

As you have seen with Sutton & Barto's book the code is mostly in Lisp. Shangtong Zhang has replicated the code in Python: https://github.com/ShangtongZhang/reinforcement-learning-an-introduction

Sudharsan and Ravichandiran wrote a book "Hands-On Reinforcement Leraning with Python" which uses OpenAI Gym and TensorFlow. You can find more information on the book along with their code repository at Hands-On Reinforcement Learning with Python

Brian O'Donnell
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    You may also want to include this repo https://github.com/dennybritz/reinforcement-learning in your answer. It contains notebooks with programming exercises where you need to implement RL algorithms. – nbro Sep 05 '20 at 21:42
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I suggest you to have a look at this repo. It contains state-of-the art algorithms, papers, frameworks, courses and some implementations. You can also check "Deep Reinforcement Learning Hands On" book examples written by Max Lapan here. This repo contains many programming and reinforcement learning examples with PyTorch framework.

dasmehdix
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  • Thanks for addressing my concern, but how does this directly answers the question? The OP was looking for resources with programming exercises, if I understood correctly. Maybe you can provide a more specific answer. – nbro Sep 07 '20 at 11:26
  • Double edited :) – dasmehdix Sep 08 '20 at 08:51