Nuts and bolts

• RL: https://rll.berkeley.edu/deeprlcourse/docs/nuts-and-bolts.pdf (https://www.youtube.com/watch?v=8EcdaCk9KaQ&app=desktop)
• http://amid.fish/reproducing-deep-rl?fbclid=IwAR1VPZm3FSTrV8BZ4UdFc2ExZy0olusmaewmloTPhpA4QOnHKRI2LLOz3mM
• https://www.reddit.com/r/reinforcementlearning/comments/7s8px9/deep_reinforcement_learning_practical_tips/
• https://stable-baselines.readthedocs.io/en/master/guide/rl_tips.html
• https://www.alexirpan.com/2018/02/14/rl-hard.html
• RL datasets https://github.com/google-research/rlds
• RL papers https://github.com/utilForever/rl-paper-studyhttps://github.com/SeungeonBaek/RL-study-2019

Cool websites:

• https://github.com/wwxFromTju/awesome-reinforcement-learning-lib
• https://www.reddit.com/r/reinforcementlearning/
• https://github.com/reinforcement-learning-kr/
• Interesting and interactive RL book
  • https://livebook.manning.com/book/deep-learning-and-the-game-of-go/chapter-12/
  • https://github.com/deep-reinforcement-learning-book
  • https://deepreinforcementlearningbook.org/
• https://github.com/wwxFromTju/awesome-reinforcement-learning-zh
• RL lab: https://rl-lab.com/

Courses

• https://deepmind.com/learning-resources/-introduction-reinforcement-learning-david-silver This one is one of the best but kinda old from 2015, but has all the fundamentals https://deepmind.com/learning-resources/reinforcement-learning-series-2021 This is the newer version, it should be much better, it is easy at the beginning but then kinda hard from mathematics background
• https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893 This is also really good and very organized and kinda interesting as they have practical projects
• https://www.coursera.org/specializations/reinforcement-learning The same comment as Udacity