orbitdeterminator VS Practical_RL

Compare orbitdeterminator vs Practical_RL and see what are their differences.

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orbitdeterminator Practical_RL
2 2
174 5,716
1.7% 0.5%
0.0 6.0
3 months ago 21 days ago
Jupyter Notebook Jupyter Notebook
MIT License The Unlicense
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

orbitdeterminator

Posts with mentions or reviews of orbitdeterminator. We have used some of these posts to build our list of alternatives and similar projects.

Practical_RL

Posts with mentions or reviews of Practical_RL. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-25.

What are some alternatives?

When comparing orbitdeterminator and Practical_RL you can also consider the following projects:

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.

awesome-rl - Reinforcement learning resources curated

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