Giter VIP home page Giter VIP logo

autokeras's Introduction

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

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

Stay Up-to-Date

Subscribe to our email list to receive announcements.

Questions and Discussions

GitHub Discussions: Ask your questions on our GitHub Discussions. It is a forum hosted on GitHub. We will monitor and answer the questions there.

Slack: Request an invitation. Use the #autokeras channel for communication.

QQ Group: Join our QQ group 1150366085. Password: akqqgroup

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!

Donation

We accept financial support on Open Collective. Thank every backer for supporting us!

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.

autokeras's People

Contributors

abgese avatar achaar avatar anselmoo avatar anuragkapale avatar bharatr21 avatar boyuangong avatar chengchengeasy avatar davidsirui avatar dependabot-preview[bot] avatar dependabot[bot] avatar dineshkumarsarangapani avatar djokester avatar droidadroit avatar ecemachine avatar fayazrahman avatar gabrieldemarmiesse avatar haifeng-jin avatar kshivendu avatar lusob avatar mandalbiswadip avatar praveenvenugopal avatar qingquansong avatar satyakesav avatar sibyjackgrove avatar t-wtnb avatar taobupt avatar tl-yang avatar xhuang31 avatar xiabenhu avatar yufei-12 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.