Skip to content

Anselmoo/autokeras

 
 

Repository files navigation

logo

codecov PyPI version Python Tensorflow contributions welcome

Official Website: autokeras.com

AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone.

Learning resources

  • A short example.
import autokeras as ak

clf = ak.ImageClassifier()
clf.fit(x_train, y_train)
results = clf.predict(x_test)

drawing     drawing

Installation

To install the package, please use the pip installation as follows:

pip3 install autokeras

Please follow the installation guide for more details.

Note: Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0.

Community

Ask your questions on our GitHub Discussions.

Contributing Code

Here is how we manage our project.

We pick the critical issues to work on from GitHub issues. They will be added to this Project. Some of the issues will then be added to the milestones, which are used to plan for the releases.

Refer to our Contributing Guide to learn the best practices.

Thank all the contributors!

The contributors

Cite this work

Haifeng Jin, Qingquan Song, and Xia Hu. "Auto-keras: An efficient neural architecture search system." Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. ACM, 2019. (Download)

Biblatex entry:

@inproceedings{jin2019auto,
  title={Auto-Keras: An Efficient Neural Architecture Search System},
  author={Jin, Haifeng and Song, Qingquan and Hu, Xia},
  booktitle={Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
  pages={1946--1956},
  year={2019},
  organization={ACM}
}

Acknowledgements

The authors gratefully acknowledge the D3M program of the Defense Advanced Research Projects Agency (DARPA) administered through AFRL contract FA8750-17-2-0116; the Texas A&M College of Engineering, and Texas A&M University.

About

AutoML library for deep learning

Resources

License

Code of conduct

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 99.2%
  • Other 0.8%