Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
AutoML library for deep learning
| Date | Stars |
|---|---|
| 2026-07-24 | 9326 |
| 2026-07-25 | 9326 |
| 2026-07-28 | 9326 |
| 2026-07-30 | 9326 |
| 2026-07-31 | 9328 |
| 2026-08-06 | 9328 |
Today
— stars today
This week
+2 stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.02%/day
<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://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 conExcerpt of 4,088 characters
Read on GitHub
Haifeng Jin
946
Qingquan Song
45
Gabriel de Marmiesse · Kyutai · France
37
30
24
19
17
16
Satya Kesav · Texas A&M University, College Station
15
13
11
10
Cheng Cheng
9
Anselm Hahn · Switzerland
8
8
RAHUL KUMAR · Google · India
8
8
7
5
Sirui(David) Ding
5
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:7d0b661d97662ed0, topic:deep-learning, topic:tensorflow