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tensorflow/tfjs

@machinelearnbot

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. Run Existing models Use TensorFlow.js model converters to run pre-existing TensorFlow models right in the browser. Retrain Existing models Retrain pre-existing ML models using sensor data connected to the browser, or other client-side data. Alternatively you can use a script tag.


Try TensorFlow.js in your browser

#artificialintelligence

In this video, Laurence Moroney (@lmoroney) shows you just how easy it is to get up and running with creating a machine learning model in JavaScript that executes right in the browser. It's the first part of a three-part series that gets you deeper into both training and executing machine learned models with TensorFlow.js, so be sure to hit that subscribe button for more!


Train your TensorFlow model on Google Cloud using TensorFlow Cloud

#artificialintelligence

Posted by Jonah Kohn and Pavithra Vijay, Software Engineers at Google TensorFlow Cloud is a python package that provides APIs for a seamless transition from debugging and training your TensorFlow code in a local environment to distributed training in Google Cloud.


TensorFlow.js : Machine Learning in Javascript

#artificialintelligence

TensorFlow.js is an open-source hardware-accelerated JavaScript library for training and deploying machine learning models. Use flexible and intuitive APIs to build models from scratch using the low-level JavaScript linear algebra library or the high-level layers API.Use TensorFlow.js model converters to run pre-existing TensorFlow models right in the browser.Retrain pre-existing ML models using sensor data connected to the browser, or other client-side data.


Faces in the Browser using TensorFlow.js

#artificialintelligence

I was honoured to be chosen to give the last talk of the day for the Machine Learning track at the Google DevFest event in Singpore on 30-November-2019. My talk, titled "Faces in the Browser using TensorFlow.js", To avoid the talk getting too theoretical, I put together a demo that everyone in the room could try for themselves: I even had two helpers on stage to show how the embeddings (aka'QR codes') for each of our faces could be clustered so that the machine could recognise the individuals later. Because the demo is in Javascript, executed entirely in the user's browser, you can examine the (trashy) code just by doing an'inspect'. If there are any questions about the presentation please ask below, or contact me using the details given on the slides themselves.