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The ability to run deep learning in the browser at production-level performance enables a huge range of new applications. We've only scratched the surface so farhttps://twitter.com/TensorFlow/status/1231987426496843777 …
Check out how 
If you use tf.keras for your deep learning models, you can: - Train on TPU or a GPU cluster in a few lines of code (fast experiment cycles) - Quickly get the best hyperparameters with Keras Tuner - Deploy on servers, on mobile devices, on embedded devices, or in the browser
We use it for in-browser annotation of medical images. Works great! Training models with Keras, then simple conversion to js model.
The browser is basically a window to a powerful cloud resource which does the heavy lifting of big datasets. Scratching a deeper surface is the ability to manipulate computation configs from your smartphone. Diggin
Great functionality!
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