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TensorFlow.js: Machine Learning for the Web and Beyond

Daniel Smilkov
Nikhil Thorat
Yannick Assogba
Ann Yuan
Nick Kreeger
Ping Yu
Kangyi Zhang
Eric Nielsen
Stan Bileschi
Charles Nicholson
Sandeep N. Gupta
Sarah Sirajuddin
Rajat Monga
SysML, Palo Alto, CA, USA (2019)


TensorFlow.js is a library for building and executing machine learning algorithms in JavaScript. TensorFlow.js models run in a web browser and in the Node.js environment. The library is part of the TensorFlow ecosystem, providing a set of APIs that are compatible with those in Python, allowing models to be ported between the Python and JavaScript ecosystems. TensorFlow.js has empowered a new set of developers from the extensive JavaScript community to build and deploy machine learning models and enabled new classes of on-device computation. This paper describes the design, API, and implementation of TensorFlow.js, and highlights some of the impactful use cases.

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