pymarl2
Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios) (by hijkzzz)
auto-sklearn
Automated Machine Learning with scikit-learn (by automl)
| pymarl2 | auto-sklearn | |
|---|---|---|
| 1 | 3 | |
| 556 | 7,403 | |
| - | 0.3% | |
| 5.0 | 1.8 | |
| 4 months ago | 4 months ago | |
| Python | Python | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" 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.
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.
pymarl2
Posts with mentions or reviews of pymarl2.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-08-17.
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MARL top conference papers are ridiculous
https://github.com/hijkzzz/pymarl2 (RIIT)
auto-sklearn
Posts with mentions or reviews of auto-sklearn.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-26.
-
Why not AutoML every tabular data?
Efficiency Ignoring the feature engineering aspects aside, a typical data scientist workflow involves trying out the different models. Some of the AutoML modules like H2O AutoML, AutoSklearn does this for you, and allow you to interpret your models. All these save so much time experimenting with the standard models.
- [R] Regularization is all you Need: Simple Neural Nets can Excel on Tabular Data
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What free AutoML library do you recommend?
If you want a more stable AutoML library, i’ll suggest auto-sklearn which optimises performance of sklearn learning algorithms.
What are some alternatives?
When comparing pymarl2 and auto-sklearn you can also consider the following projects:
nlp-recipes - Natural Language Processing Best Practices & Examples
autogluon - Fast and Accurate ML in 3 Lines of Code
ai-economist - Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
Auto-PyTorch - Automatic architecture search and hyperparameter optimization for PyTorch