Paris Machine Learning Meetup #2 Season 4: Emotional AI, Regaind, Health Knowledge....

So today is Paris Machine Learning Meetup #2 Season 4 and it'll be hosted and sponsored by Vente-privée, woohoo ! Tonight we'll be talking about Emotional AI, Training set for image in Deep Learning, Health Knowledge, ML at Vente-Privée....and we will have a new feature. A debate of sorts. The streaming video is below and the presentation should be available before the meetup.

Voici le programme pour l'instant:

• 18:30 Franck Bardol, Igor Carron, intro  (newsletter October 2016)
• 18:45 Clementine Delphin, Startup Weekend Artificial Intelligence (slides pdf version, 2 mins)
• 18:55 Olivier Dolle, Ivan Vukic, Antoine Deblonde Vente-privée, Machine Learning at Vente-Privée, 
• 19:15 Frederico Quintao, Health Knowledge Framework for the Web, 

In this presentation, I will show a framework for the classification of medical knowledge on the web, and where some current ML approaches to learn public health metrics from query logs/docs fit in the framework. This is somehow tied to my work at Google, where I was the global eng lead of the Health Search team for almost 5 years.

• 19:35 Gregory Renard, Xbrain,  "Emotional AI", http://www.people2vec.org/
• 20:00 Arnaud Laurenty, Regaind.io What I wish a ninja data scientist had told me before we started building our datasets :)

Building machine learning models starts by generating a high quality dataset adapted to your task. Sometimes, you get all the data from a service that is already in production, and you mostly need to analyze it and clean it thoroughly. Sometimes, you have nothing at all, or you decide that you want to start everything from scratch. 

At Regaind, we have built an artificial intelligence that understands what photos matter to people in terms of content, action and aesthetic quality. You may try it out by having fun a virtual photo coach at https://keegan.regaind.io :)

Creating our datasets has been a painful, expensive and time-consuming experience. We've paid for 20,000 hours of manual labelling and we've done mistakes along the way. We've worked with employees in CDD, with a crowdsourcing platform, and with offshore partners. In this totally unglamorous talk, we'll provide you with a humble feedback on the whole process, hoping that our experience will reduce your pain: cost, speed, quality, timing, legal issues, best practices...

• 20:20 Debate with François Némo, "Pourquoi l'Europe est-elle absente de la guerre des plateformes ?" (pdf version)

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