Awesome

AutoKeras: An AutoML system based on Keras. It is developed by <a href="http://faculty.cs.tamu.edu/xiahu/index.html" target="_blank" rel="nofollow">DATA Lab</a> 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)

Official website tutorials.
The book of Automated Machine Learning in Action.
The LiveProjects of Image Classification with AutoKeras.

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!

Cite this work

Haifeng Jin, François Chollet, Qingquan Song, and Xia Hu. "AutoKeras: An AutoML Library for Deep Learning." the Journal of machine Learning research 6 (2023): 1-6. (Download)

Biblatex entry:

@article{JMLR:v24:20-1355,
  author  = {Haifeng Jin and François Chollet and Qingquan Song and Xia Hu},
  title   = {AutoKeras: An AutoML Library for Deep Learning},
  journal = {Journal of Machine Learning Research},
  year    = {2023},
  volume  = {24},
  number  = {6},
  pages   = {1--6},
  url     = {http://jmlr.org/papers/v24/20-1355.html}
}

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.