@SeatGeek: Deep Learning on Device & SeatGeek iMessage App

SeatGeek's building security team requires the RSVP list by EOD Wednesday, February 8th. Please make sure to RSVP by then!

SPEAKERS:

Jack Rogers, Mobile Software Engineer at Clarifai

Deep Learning on Device

It’s 2017, and computers can see. Still, it can be challenging to integrate deep learning into your apps. I’ll go over the best approaches, including Tensorflow, and show how the new Clarifai SDK makes it easy to train models in real-time on device and share them between users.

Jack is a mobile software engineer at Clarifai, where he works on bringing deep learning onto mobile devices. He has contributed to Signal, and helped build Clarifai’s intelligent photos app, Forevery. He enjoys chilling on his double decker couch.

Steven Lehrburger, iOS Engineer at SeatGeek

SeatGeek iMessage App

SeatGeek’s iMessage App takes the most social parts of the product and makes them available within the iOS Messages app. Users can search for events to discuss with their friends, and then send the tickets quickly and easily without the hassle of PDFs or printing (blog post with screenshots (http://chairnerd.seatgeek.com/see-more-events-together-with-the-new-seatgeek-imessage-app/)). The app was written in Objective-C for a tight deadline, and you’ll hear about how we simplified existing features to optimize for both real-world usefulness and minimal development effort.

Steven (https://twitter.com/lehrblogger) started developing for iOS in 2009 and – after forays into Javascript in the browser, Python for chat bots, and Chef on AWS – returned to it in 2014. He studied offline spaces at Stanford's architecture program and online spaces at NYU's Interactive Telecommunications Program, and now helps people attend more live events at SeatGeek (http://seatgeek.com/).