machine_learning_examples VS stable-baselines

Compare machine_learning_examples vs stable-baselines and see what are their differences.

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machine_learning_examples stable-baselines
3 10
8,040 4,000
- -
5.9 0.0
3 months ago over 1 year ago
Python Python
- MIT License
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.

machine_learning_examples

Posts with mentions or reviews of machine_learning_examples. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-25.
  • Doubt about numpy's eigen calculation
    2 projects | /r/learnmachinelearning | 25 May 2023
    Does that mean that the example I found on the internet is wrong (I think it comes from a DL Course, so I'd imagine it is not wrong)? or does it mean that I am comparing two different things? I guess this has to deal with right and left eigen vectors as u/JanneJM pointed out in her comment?
    2 projects | /r/learnmachinelearning | 25 May 2023
    My example comes from here, but I added cosmetic/debug changes: https://github.com/lazyprogrammer/machine_learning_examples/blob/master/numpy_class/exercises/ex1.py

stable-baselines

Posts with mentions or reviews of stable-baselines. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-28.

What are some alternatives?

When comparing machine_learning_examples and stable-baselines you can also consider the following projects:

stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

Tic-Tac-Toe-Gym - This is the Tic-Tac-Toe game made with Python using the PyGame library and the Gym library to implement the AI with Reinforcement Learning

gym

DI-engine - OpenDILab Decision AI Engine

kaggle-environments

soft-actor-critic - Implementation of the Soft Actor Critic algorithm using Pytorch.

open-ai - OpenAI PHP SDK : Most downloaded, forked, contributed, huge community supported, and used PHP (Laravel , Symfony, Yii, Cake PHP or any PHP framework) SDK for OpenAI GPT-3 and DALL-E. It also supports chatGPT-like streaming. (ChatGPT AI is supported)

SuperSuit - A collection of wrappers for Gymnasium and PettingZoo environments (being merged into gymnasium.wrappers and pettingzoo.wrappers

gym-battleship - Battleship environment for reinforcement learning tasks