Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Automated Machine Learning with scikit-learn
| Date | Stars |
|---|---|
| 2026-07-31 | 8126 |
| 2026-08-02 | 8126 |
| 2026-08-03 | 8127 |
| 2026-08-06 | 8127 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# auto-sklearn
**auto-sklearn** is an automated machine learning toolkit and a drop-in replacement for a [scikit-learn](https://scikit-learn.org) estimator.
Find the documentation **[here](https://automl.github.io/auto-sklearn/)**. Quick links:
* [Installation Guide](https://automl.github.io/auto-sklearn/master/installation.html)
* [Releases](https://automl.github.io/auto-sklearn/master/releases.html)
* [Manual](https://automl.github.io/auto-sklearn/master/manual.html)
* [Examples](https://automl.github.io/auto-sklearn/master/examples/index.html)
* [API](https://automl.github.io/auto-sklearn/master/api.html)
## auto-sklearn in one image
## auto-sklearn in four lines of code
```python
import autosklearn.classification
cls = autosklearn.classification.AutoSklearnClassifier()
cls.fit(X_train, y_train)
predictions = cls.predict(X_test)
```
## Relevant publications
If you use auto-sklearn in scientific publications, we would appreciate citations.
**Efficient and Robust Automated Machine Learning**
*Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum and Frank Hutter*
Advances in Neural Information Processing Systems 28 (2015)
[Link](https://papers.neurips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf) to publication.
```
@inproceedings{feurer-neurips15a,
title = {Efficient and Robust Automated Machine Learning},
author = {Feurer, Matthias and Klein, Aaron and Eggensperger, Katharina and Springenberg, Jost and Blum, Manuel and Hutter, Frank},
booktitle = {Advances in Neural Information Processing Systems 28 (2015)},
pages = {2962--2970},
year = {2015}
}
```
----------------------------------------
**Auto-Sklearn 2.0: The Next Generation**
*Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer and Frank Hutter**
arXiv:2007.04074 [cs.LG], 2020
[Link](https://arxiv.org/abs/2007.04074) to publication.
```
@article{feurer-arxiv20a,
title = {Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning},
author = {Feurer, Matthias and Eggensperger, Katharina and Falkner, Stefan and Lindauer, Marius and Hutter, Frank},
booktitle = {arXiv:2007.04074 [cs.LG]},
year = {2020}
}
```
----------------------------------------
Also, have a look at the blog on [automl.org](https://automl.org) where we regularly release blogposts.
Excerpt of 2,439 characters
Read on GitHub
1.6k
Eddie Bergman · dbtune.com · Sweden
183
154
Aaron Klein · ELLIS Institute Tübingen
82
Francisco Rivera Valverde · University of Freiburg
81
44
42
15
14
11
10
10
Herilalaina Rakotoarison
10
9
6
6
4
Jirka Borovec · Czech Republic
4
4
4
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4360eba80d18acfb, llm:Topics: automated-machine-learning, automl, bayesian-optimization, hyperparameter-optimization, hyperparameter-search, hyperparameter-tuning, meta-learning, metalearning, scikit-learn, smac; Description/README: 'Automated Machine Learning with scikit-learn', toolkit/drop-in replacement, AutoSklearnClassifier usage example.
matched fp:4360eba80d18acfb, llm:Topics: automated-machine-learning, automl, bayesian-optimization, hyperparameter-optimization, hyperparameter-search, hyperparameter-tuning, meta-learning, metalearning, scikit-learn, smac; Description/README: 'Automated Machine Learning with scikit-learn', toolkit/drop-in replacement, AutoSklearnClassifier usage example.
matched fp:4360eba80d18acfb, llm:Topics: automated-machine-learning, automl, bayesian-optimization, hyperparameter-optimization, hyperparameter-search, hyperparameter-tuning, meta-learning, metalearning, scikit-learn, smac; Description/README: 'Automated Machine Learning with scikit-learn', toolkit/drop-in replacement, AutoSklearnClassifier usage example.