October 28–31, 2019

Schedule: JavaScript sessions

Running TensorFlow in the web browser and under Node.js

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11:50am12:30pm Wednesday, October 30, 2019
Location: Grand Ballroom A/B
Zac Yung-Chun Liu (Stanford University), Andy Chamberlin (Stanford University), Susanne Sokolow (Stanford University | UC Santa Barbara), Giulio De Leo (Stanford University), Ton Ngo (IBM)
Schistosomiasis is a debilitating parasitic disease that affects more than 250 million people worldwide. Zac Yung-Chun Liu, Andy Chamberlin, Susanne Sokolow, Giulio De Leo, and Ton Ngo detail how to build and deploy deep learning applications to detect disease transmission hotspots, make interventions more efficient and scalable, and help governments and stakeholders make data-driven decisions. Read more.
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11:00am11:40am Thursday, October 31, 2019
Location: Grand Ballroom E
va barbosa (IBM), Paul Van Eck (IBM)
Va Barbosa and Paul Van Ec highlight the benefits of using TensorFlow.js and Node-RED together as an educational tool to engage developers and provide you with a powerful, creativity-inspiring platform for interacting and developing with machine learning models. Read more.
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11:50am12:30pm Thursday, October 31, 2019
Location: Grand Ballroom E
Victor Dibia (Cloudera Fast Forward Labs)
Victor Dibia explores the state of the art for machine learning in the browser using Tensorflow.js and dives into its use in the design of Handtrack.js—a library for prototyping real-time hand-tracking interactions in the browser. Read more.
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1:40pm2:20pm Thursday, October 31, 2019
Location: Grand Ballroom E
Babusi Nyoni (Triple Black)
In 2018 Triple Black created a dance app that used Tensorflow.js-powered pose estimation on mobile phones to rate a popular South African dance known as "iVosho." Babusi Nyoni unpacks the possibilities for AI in disadvantaged African communities and explains how and why the company turned this dance app into a tool to diagnose Parkinson's disease. Read more.

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