Unlocking the power of ML for your JavaScript applications with TensorFlow.js

Unlocking the power of ML for your JavaScript applications with TensorFlow.js

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 Javascript platforms

TensorFlow.js is an open-source hardware-accelerated JavaScript library for training and deploying machine learning models. Develop ML in the Browser. Use flexible and intuitive APIs to build models from scratch using the low-level JavaScript linear algebra library or the high-level layers API.

TensorFlow.js is a library for training and deploying machine learning models in the browser and in Node.js, and offers unique opportunities for JavaScript developers. 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. Come see live demos of our models and featured applications (Wechat virtual try-on plugin from L'oreal, and a radiology diagnostic tool from Mila).

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<strong>TensorFlow.js is the recently-released JavaScript version of TensorFlow that runs in the browser and Node.js. In this talk, the team introduced the TensorFlow.js ML framework, and showed with demo on how to perform the complete machine-learning workflow, including the training, client-side deployment, and transfer learning.</strong>

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Machine Learning in JavaScript with TensorFlow.js

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. Interested in using Machine Learning in JavaScript applications and websites? 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.