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TensorFlow.js is a library for machine learning in JavaScript

Develop ML models in JavaScript, and use ML directly in the browser or in Node.js.

See tutorials

Tutorials show you how to use TensorFlow.js with complete, end-to-end examples.

See models

Pre-trained, out-of-the-box models for common use cases.

See demos

Live demos and examples run in your browser using TensorFlow.js.

How it works

Run existing models

Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js.

Retrain existing models

Retrain pre-existing ML models using your own data.

Develop ML with JavaScript

Build and train models directly in JavaScript using flexible and intuitive APIs.


Performance RNN

Enjoy a real-time piano performance by a neural network.

Webcam Controller

Play Pac-Man using images trained in your browser.

Move Mirror

Explore pictures in a fun new way, just by moving around.

News & announcements

See updates to help you with your work, and subscribe to our monthly TensorFlow newsletter to get the latest announcements sent directly to your inbox.

Oct 24, 2019 
Deploy AutoML models to TF.js

The beta version of TF.js integration with AutoML is launched! Build image classification and object detection models using Cloud AutoML without any coding, and download TF.js compatible versions directly.

Oct 24, 2019 
React Native Support

We have launched the alpha version of first-class React Native support for TF.js, including WebGL acceleration on supported platforms. Learn how to bring performant ML into your React Native app.

Jul 21, 2019 
TensorFlow Meets

On this episode of TensorFlow Meets, Laurence talks with Yannick Assogba, software engineer on the TensorFlow.js team. Learn about training in the browser, and how TensorFlow.js pre-trained and custom models can help you solve your ML use cases.

May 8, 2019 
Machine Learning Magic for Your JavaScript Application (I/O'19)

In this talk, you will learn about the TensorFlow.js ecosystem: how to bring an existing machine learning model into your JS app, re-train the model using your data, and go beyond the browser to other JS platforms.