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README.md

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**auto-sklearn** is an automated machine learning toolkit and a drop-in replacement for a [scikit-learn](https://scikit-learn.org) estimator.
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Find the documentation **[here](http://automl.github.io/auto-sklearn/)**. Quick links:
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Find the documentation **[here](https://automl.github.io/auto-sklearn/)**. Quick links:
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* [Installation Guide](https://automl.github.io/auto-sklearn/master/installation.html)
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* [Releases](https://automl.github.io/auto-sklearn/master/releases.html)
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* [Manual](https://automl.github.io/auto-sklearn/master/manual.html)
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*Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum and Frank Hutter*
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Advances in Neural Information Processing Systems 28 (2015)
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[Link](http://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf) to publication.
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[Link](https://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf) to publication.
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```
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@inproceedings{feurer-neurips15a,
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title = {Efficient and Robust Automated Machine Learning},
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Also, have a look at the blog on [automl.org](automl.org) where we regularly release blogposts.
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Also, have a look at the blog on [automl.org](https://automl.org) where we regularly release blogposts.

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