# auto-sklearn

> Automated Machine Learning with scikit-learn

**Wikidata**: [Q120703207](https://www.wikidata.org/wiki/Q120703207)  
**Source**: https://4ort.xyz/entity/auto-sklearn

## Summary
Auto-sklearn is an Automated Machine Learning toolkit built with Python and scikit-learn. It automates the process of applying machine learning to real-world problems by handling algorithm selection, hyperparameter tuning, and model evaluation automatically.

## Key Facts
- Auto-sklearn is free software distributed under a 3-clause BSD License
- It is implemented entirely in Python
- The first version (0.1) was released on October 17, 2016
- Source code is available at https://github.com/automl/auto-sklearn
- The official website is https://automl.github.io/auto-sklearn/
- Multiple versions have been released between 2016 and 2019, ranging from 0.1 to 0.5.2
- It is academically described as "Efficient and Robust Automated Machine Learning"

## FAQs
### Q: What is auto-sklearn?
A: Auto-sklearn is an automated machine learning toolkit built with Python and scikit-learn that automates the process of applying machine learning to real-world problems by handling algorithm selection and tuning automatically.

### Q: Is auto-sklearn free to use?
A: Yes, auto-sklearn is free software distributed under the terms of a 3-clause BSD License, allowing users to freely run, study, change and distribute it and modified versions.

### Q: When was auto-sklearn first released?
A: The first version (0.1) of auto-sklearn was released on October 17, 2016.

### Q: Where can I find the source code for auto-sklearn?
A: The source code for auto-sklearn is available on GitHub at https://github.com/automl/auto-sklearn.

## Why It Matters
Auto-sklearn democratizes machine learning by automating complex processes that would normally require significant expertise in algorithm selection, hyperparameter tuning, and model evaluation. This accessibility enables developers and data scientists to apply high-quality machine learning solutions without needing deep technical knowledge in machine learning. By reducing the barriers to implementing effective machine learning models, auto-sklearn has likely accelerated its adoption across various industries and research fields, making machine learning more practical for real-world applications.

## Notable For
- Being an automated machine learning toolkit specifically built with Python and scikit-learn
- Providing automated algorithm selection and hyperparameter tuning
- Having regular version releases from 2016 to 2019
- Being free software with a permissive 3-clause BSD License
- Being academically recognized as "Efficient and Robust Automated Machine Learning"

## Body
### Overview
Auto-sklearn is an automated machine learning toolkit that automates the process of applying machine learning to real-world problems by handling algorithm selection, hyperparameter tuning, and model evaluation automatically.

### Technical Details
- Programming Language: Python
- Licensing: 3-clause BSD License
- Category: Free software
- Instance of: Free software

### Development
- Source Code Repository: https://github.com/automl/auto-sklearn
- Official Website: https://automl.github.io/auto-sklearn/
- Download URL: https://github.com/automl/auto-sklearn/releases

### Version History
- Version 0.1: Released October 17, 2016
- Version 0.1.1: Released November 28, 2016
- Version 0.1.3: Released February 24, 2017
- Version 0.2.0: Released May 16, 2017
- Version 0.2.1: Released October 4, 2017
- Version 0.3.0: Released January 5, 2018
- Version 0.4.0: Released June 19, 2018
- Version 0.4.1: Released November 12, 2018
- Version 0.4.2: Released December 13, 2018
- Version 0.5.2: Released May 13, 2019

### Recognition
Auto-sklearn is academically described in the source "Efficient and Robust Automated Machine Learning."

## References

1. [Release 0.1. 2016](https://github.com/automl/auto-sklearn/releases/tag/0.1)
2. [Release 0.1.1. 2016](https://github.com/automl/auto-sklearn/releases/tag/0.1.1)
3. [Release 0.1.3. 2017](https://github.com/automl/auto-sklearn/releases/tag/0.1.3)
4. [Release 0.2.0. 2017](https://github.com/automl/auto-sklearn/releases/tag/v.0.2.0)
5. [Release 0.2.1. 2017](https://github.com/automl/auto-sklearn/releases/tag/v.0.2.1)
6. [Release 0.3.0. 2018](https://github.com/automl/auto-sklearn/releases/tag/v.0.3.0)
7. [Release 0.4.0. 2018](https://github.com/automl/auto-sklearn/releases/tag/v.0.4.0)
8. [Release 0.4.1. 2018](https://github.com/automl/auto-sklearn/releases/tag/v.0.4.1)
9. [Release 0.4.2. 2018](https://github.com/automl/auto-sklearn/releases/tag/v.0.4.2)
10. [Release 0.5.2. 2019](https://github.com/automl/auto-sklearn/releases/tag/v.0.5.2)
11. [Release 0.6.0. 2020](https://github.com/automl/auto-sklearn/releases/tag/v.0.6.0)
12. [Release 0.7.0. 2020](https://github.com/automl/auto-sklearn/releases/tag/v.0.7.0)
13. [Release 0.7.1. 2020](https://github.com/automl/auto-sklearn/releases/tag/v.0.7.1)
14. [Release 0.8.0. 2020](https://github.com/automl/auto-sklearn/releases/tag/v.0.8.0)
15. [Release 0.10.0. 2020](https://github.com/automl/auto-sklearn/releases/tag/v0.10.0)
16. [Release 0.11.0. 2020](https://github.com/automl/auto-sklearn/releases/tag/v0.11.0)
17. [Release 0.11.1. 2020](https://github.com/automl/auto-sklearn/releases/tag/v0.11.1)
18. [Release 0.12.0. 2020](https://github.com/automl/auto-sklearn/releases/tag/v0.12.0)
19. [Release 0.12.1. 2021](https://github.com/automl/auto-sklearn/releases/tag/v0.12.1)
20. [Release 0.12.2. 2021](https://github.com/automl/auto-sklearn/releases/tag/v0.12.2)
21. [Release 0.12.3. 2021](https://github.com/automl/auto-sklearn/releases/tag/v0.12.3)
22. [Release 0.12.4. 2021](https://github.com/automl/auto-sklearn/releases/tag/v0.12.4)
23. [Release 0.12.5. 2021](https://github.com/automl/auto-sklearn/releases/tag/v0.12.5)
24. [Release 0.12.6. 2021](https://github.com/automl/auto-sklearn/releases/tag/v0.12.6)
25. [Release 0.12.7. 2021](https://github.com/automl/auto-sklearn/releases/tag/v0.12.7)
26. [Release 0.14.1. 2021](https://github.com/automl/auto-sklearn/releases/tag/v0.14.1)
27. [Release 0.14.3. 2021](https://github.com/automl/auto-sklearn/releases/tag/v0.14.3)
28. [Release 0.14.4. 2022](https://github.com/automl/auto-sklearn/releases/tag/v0.14.4)
29. [Release 0.14.5. 2022](https://github.com/automl/auto-sklearn/releases/tag/v0.14.5)
30. [Release 0.14.6. 2022](https://github.com/automl/auto-sklearn/releases/tag/v0.14.6)
31. [Release 0.14.7. 2022](https://github.com/automl/auto-sklearn/releases/tag/v0.14.7)
32. [Release 0.15.0. 2023](https://github.com/automl/auto-sklearn/releases/tag/v0.15.0)
33. [Source](https://api.github.com/repos/automl/auto-sklearn)