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Machine Learning in JavaScript with TensorFlow.js

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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. If you're a Javascript developer who's new to ML, TensorFlow.js is a great way to begin learning. Or, if you're a ML developer who's new to Javascript, read on to learn more about new opportunities for in-browser ML. We're excited to introduce TensorFlow.js, an open-source library you can use to define, train, and run machine learning models entirely in the browser, using Javascript and a high-level layers API.


Bringing Artificial Intelligence to the Browser with TensorFlow.js

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TensorFlow.js allows web developers to easily build and run browser-based Artificial Intelligence apps using only JavaScript. Are you a web developer interested in Artificial Intelligence (AI)? Want to easily build some sweet AI apps entirely in JavaScript that run anywhere, without the headache of tedious installs, hosting on cloud services, or working with Python? Then TensorFlow.js is for you! Developers can now more easily leverage Artificial Intelligence to build uniquely responsive apps that react to user inputs such as voice or facial expression in real time, or to create smarter apps that learn from user behaviour and adapt.


TensorFlow.js: Machine learning for the web and beyond

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If machine learning and ML models are to pervade all of our applications and systems, then they'd better go to where the applications are rather than the other way round. Increasingly, that means JavaScript – both in the browser and on the server. TensorFlow.js brings TensorFlow and Keras to the the JavaScript ecosystem, supporting both Node.js and browser-based applications. As well as programmer accessibility and ease of integration, running on-device means that in many cases user data never has to leave the device. On-device computation has a number of benefits, including data privacy, accessibility, and low-latency interactive applications.


Introducing TensorFlow.js: Machine Learning in Javascript

#artificialintelligence

We're excited to introduce TensorFlow.js, an open-source library you can use to define, train, and run machine learning models entirely in the browser, using Javascript and a high-level layers API. If you're a Javascript developer who's new to ML, TensorFlow.js is a great way to begin learning. Or, if you're a ML developer who's new to Javascript, read on to learn more about new opportunities for in-browser ML. In this post, we'll give you a quick overview of TensorFlow.js, and getting started resources you can use to try it out. Running machine learning programs entirely client-side in the browser unlocks new opportunities, like interactive ML!


TensorFlow.js puts machine learning in the browser

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Google's TensorFlow open source machine learning library has been extended to JavaScript with Tensorflow.js, a JavaScript library for deploying machine learning models in the browser. A WebGL-accelerated library, Tensorflow.js also works with the Node.js With machine learning directly in the browser, there is no need for drivers; developers can just run code. The project, which features an ecosystem of JavaScript tools, evolved from the Deeplearn.js APIs can be used to build models using the low-level JavaScript linear algebra library or the higher-level layers API.