https://github.com/learnables/torchml

Scikit-learn implemented with PyTorch
https://github.com/learnables/torchml

machine-learning pytorch scikit-learn

Last synced: about 1 month ago
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Scikit-learn implemented with PyTorch

• Host: GitHub
• URL: https://github.com/learnables/torchml
• Owner: learnables
• License: mit
• Created: 2022-04-16T03:35:16.000Z (about 3 years ago)
• Default Branch: master
• Last Pushed: 2023-05-30T20:04:20.000Z (almost 2 years ago)
• Last Synced: 2025-03-27T21:39:02.943Z (about 2 months ago)
• Topics: machine-learning, pytorch, scikit-learn
• Language: Python
• Homepage: http://learnables.net/torchml/
• Size: 23.2 MB
• Stars: 8
• Watchers: 4
• Forks: 1
• Open Issues: 16
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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![Test Status](https://github.com/learnables/torchml/workflows/Testing/badge.svg?branch=master)

`torchml` implements the scikit-learn API on top of PyTorch.

This means we automatically get GPU support for scikit-learn and, when possible, differentiability.

## Resources

- GitHub: [github.com/learnables/torchml](http://github.com/learnables/torchml)

- Documentation: [learnables.net/torchml](http://learnables.net/torchml/)

- Tutorials: [learnables.net/torchml/tutorials](http://learnables.net/torchml/tutorials/linear_model/)

- Examples: [learnables.net/torchml/examples](https://github.com/learnables/torchml/tree/master/examples)

## Getting Started

`pip install torchml`

### Minimal Linear Regression Example

~~~python

import torchml as ml

(X_train, y_train), (X_test, y_test) = generate_data()

# API closely follows scikit-learn

linreg = ml.linear_model.LinearRegression()

linreg.fit(X_train, y_train)

linreg.predict(X_test)

~~~

## Changelog

A human-readable changelog is available in the [CHANGELOG.md](./CHANGELOG.md) file.

## Citing

To cite `torchml` repository in your academic publications, please use the following reference.

>  Sébastien M. R. Arnold, Lucy Xiaoyang Shi, Xinran Gao, Zhiheng Zhang, and Bairen Chen. 2023. "torchml: a scikit-learn implementation on top of PyTorch".

You can also use the following Bibtex entry:

~~~bib

@misc{torchml,

  author={Arnold, S{\'e}bastien M R and Shi, Lucy Xiaoyang and Gao, Xinran and Zhang, Zhiheng and Chen, Bairen},

  title={torchml: A scikit-learn implementation on top of PyTorch},

  year={2023},

  url={https://github.com/learnables/torchml},

}

~~~