<p align="center">
<img width="500" alt="logo" src="https://autokeras.com/img/row_red.svg"/>
</p>
[](https://github.com/keras-team/autokeras/actions?query=workflow%3ATests+branch%3Amaster)
[](https://codecov.io/gh/keras-team/autokeras)
[](https://badge.fury.io/py/autokeras)
[](https://www.python.org/downloads/)
[](https://www.tensorflow.org/versions)
[](https://github.com/keras-team/autokeras/issues)
Official Website: [autokeras.com](https://autokeras.com)
##
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.
```python
import autokeras as ak
clf = ak.ImageClassifier()
clf.fit(x_train, y_train)
results = clf.predict(x_test)
```
* [Official website tutorials](https://autokeras.com/tutorial/overview/).
* The book of [*Automated Machine Learning in Action*](https://www.manning.com/books/automated-machine-learning-in-action?query=automated&utm_source=jin&utm_medium=affiliate&utm_campaign=affiliate&a_aid=jin).
* The LiveProjects of [*Image Classification with AutoKeras*](https://www.manning.com/liveprojectseries/autokeras-ser).
<p align="center">
<a href="https://www.manning.com/books/automated-machine-learning-in-action?query=automated&utm_source=jin&utm_medium=affiliate&utm_campaign=affiliate&a_aid=jin"><img src="https://images.manning.com/360/480/resize/book/0/fc56aaf-b2ba-4ef4-85b3-4a31edbe8ecc/Song-AML-HI.png" alt="drawing" width="266"/></a>
 
 
<a href="https://www.manning.com/liveprojectseries/autokeras-ser"><img src="https://images.manning.com/360/480/resize/liveProjectSeries/9/38c715a-0c8c-4f66-b440-83d29993877a/ImageClassificationwithAutoKeras.jpg" alt="drawing" width="250"/></a>
</p>
## Installation
To install the package, please use the `pip` installation as follows:
```shell
pip3 install autokeras
```
Please follow the [installation guide](https://autokeras.com/install) 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](https://github.com/keras-team/autokeras/discussions).
## Contributing Code
Here is how we manage our project.
We pick the critical issues to work on from [GitHub issues](https://github.com/keras-team/autokeras/issues).
They will be added to this [Project](https://github.com/keras-team/autokeras/projects/3).
Some of the issues will then be added to the [milestones](https://github.com/keras-team/autokeras/milestones),
which are used to plan for the releases.
Refer to our [Contributing Guide](https://autokeras.com/contributing/) to learn the best practices.
Thank all the contributors!
[](https://github.com/keras-team/autokeras/graphs/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](http://jmlr.org/papers/v24/20-1355.html))
Biblatex entry:
```bibtex
@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.
Raw data
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"description": "<p align=\"center\">\n <img width=\"500\" alt=\"logo\" src=\"https://autokeras.com/img/row_red.svg\"/>\n</p>\n\n[](https://github.com/keras-team/autokeras/actions?query=workflow%3ATests+branch%3Amaster)\n[](https://codecov.io/gh/keras-team/autokeras)\n[](https://badge.fury.io/py/autokeras)\n[](https://www.python.org/downloads/)\n[](https://www.tensorflow.org/versions)\n[](https://github.com/keras-team/autokeras/issues)\n\nOfficial Website: [autokeras.com](https://autokeras.com)\n\n##\nAutoKeras: An AutoML system based on Keras.\nIt 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.\nThe goal of AutoKeras is to make machine learning accessible to everyone.\n\n## Learning resources\n\n* A short example.\n\n```python\nimport autokeras as ak\n\nclf = ak.ImageClassifier()\nclf.fit(x_train, y_train)\nresults = clf.predict(x_test)\n```\n\n* [Official website tutorials](https://autokeras.com/tutorial/overview/).\n* The book of [*Automated Machine Learning in Action*](https://www.manning.com/books/automated-machine-learning-in-action?query=automated&utm_source=jin&utm_medium=affiliate&utm_campaign=affiliate&a_aid=jin).\n* The LiveProjects of [*Image Classification with AutoKeras*](https://www.manning.com/liveprojectseries/autokeras-ser).\n<p align=\"center\">\n<a href=\"https://www.manning.com/books/automated-machine-learning-in-action?query=automated&utm_source=jin&utm_medium=affiliate&utm_campaign=affiliate&a_aid=jin\"><img src=\"https://images.manning.com/360/480/resize/book/0/fc56aaf-b2ba-4ef4-85b3-4a31edbe8ecc/Song-AML-HI.png\" alt=\"drawing\" width=\"266\"/></a>\n \n \n<a href=\"https://www.manning.com/liveprojectseries/autokeras-ser\"><img src=\"https://images.manning.com/360/480/resize/liveProjectSeries/9/38c715a-0c8c-4f66-b440-83d29993877a/ImageClassificationwithAutoKeras.jpg\" alt=\"drawing\" width=\"250\"/></a>\n</p>\n\n\n## Installation\n\nTo install the package, please use the `pip` installation as follows:\n\n```shell\npip3 install autokeras\n```\n\nPlease follow the [installation guide](https://autokeras.com/install) for more details.\n\n**Note:** Currently, AutoKeras is only compatible with **Python >= 3.7** and **TensorFlow >= 2.8.0**.\n\n## Community\n\nAsk your questions on our [GitHub Discussions](https://github.com/keras-team/autokeras/discussions).\n\n## Contributing Code\n\nHere is how we manage our project.\n\nWe pick the critical issues to work on from [GitHub issues](https://github.com/keras-team/autokeras/issues).\nThey will be added to this [Project](https://github.com/keras-team/autokeras/projects/3).\nSome of the issues will then be added to the [milestones](https://github.com/keras-team/autokeras/milestones),\nwhich are used to plan for the releases.\n\nRefer to our [Contributing Guide](https://autokeras.com/contributing/) to learn the best practices.\n\nThank all the contributors!\n\n[](https://github.com/keras-team/autokeras/graphs/contributors)\n\n## Cite this work\n\nHaifeng Jin, Fran\u00e7ois Chollet, Qingquan Song, and Xia Hu. \"AutoKeras: An AutoML Library for Deep Learning.\" *the Journal of machine Learning research* 6 (2023): 1-6. ([Download](http://jmlr.org/papers/v24/20-1355.html))\n\nBiblatex entry:\n\n```bibtex\n@article{JMLR:v24:20-1355,\n author = {Haifeng Jin and Fran\u00e7ois Chollet and Qingquan Song and Xia Hu},\n title = {AutoKeras: An AutoML Library for Deep Learning},\n journal = {Journal of Machine Learning Research},\n year = {2023},\n volume = {24},\n number = {6},\n pages = {1--6},\n url = {http://jmlr.org/papers/v24/20-1355.html}\n}\n```\n\n## Acknowledgements\n\nThe 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.\n",
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