awesome-rl
Practical_RL
awesome-rl | Practical_RL | |
---|---|---|
4 | 2 | |
8,645 | 5,753 | |
0.5% | 1.1% | |
0.0 | 6.0 | |
12 months ago | 24 days ago | |
Jupyter Notebook | ||
- | The Unlicense |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
awesome-rl
-
How to code an overall directive?
You can also find a great number of already-built examples of various RL algorithms here: https://github.com/aikorea/awesome-rl
-
Any good begynder books about reinforcement learning
and also here's a curated list of RL resources that I got off this subreddit a while ago: https://github.com/aikorea/awesome-rl
-
A collection of books, surveys, and courses on RL Theory and related areas.
Or just read this https://github.com/aikorea/awesome-rl
-
Alternatives to OpenAI’s spinning up?
also there is a compilation of a lot of online courses and materials you should check it out !!!
Practical_RL
- [D] implementation of MCTS in Python
-
Alternatives to OpenAI’s spinning up?
there is this great github repo where there are lectures and other resources, and have a week by week jupyter notebooks where they explain and code with homeworks at the very end of it. is basics and deepRL, but just dqn and DDPG/ppo but i think will give you good start in the topic for later star working on your own.
What are some alternatives?
webdataset - A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
FunMatch-Distillation - TF2 implementation of knowledge distillation using the "function matching" hypothesis from https://arxiv.org/abs/2106.05237.
alpha-zero-general - A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
labml - 🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
redisai-examples - RedisAI showcase
TensorFlow-Tutorials - TensorFlow Tutorials with YouTube Videos
YPDL-Build-a-movie-recommendation-engine-with-TensorFlow - In this tutorial, we are going to build a Restricted Boltzmann Machine using TensorFlow that will give us recommendations based on movies that have been watched already. The datasets we are going to use are acquired from GroupLens and contains movies, users, and movie ratings by these users.
rl-trading - Using Reinforcement Learning agents as Algorithmic Traders
AIrsenal - Machine learning Fantasy Premier League team
awesome-RLHF - A curated list of reinforcement learning with human feedback resources (continually updated)
PX4-user_guide - PX4 User Guide