Ce Soir: Paris Machine Learning Meetup #1, Season 2, A New Beginning (Snips, Nomo, Clustaar and more)

Once again with Franck, we have decided to do a second season of the pretty successul season 1 of the Paris Machine Learning Meetup. We have about 1200 members and growing. The twitter hashtag for tonight's meetup is #MLParis.

The YouTube page is here, while the Google Hangout Event page is here.

Resources for the Paris Machine Learning group other than ones on Meetup.com include the LinkedIn group, Google+ group and the Archives of the meetup.

A big thank you to DojoEvents for hosting us.

Here is the tentative list of talks and abstracts for tonight's meetup:

+ Franck Bardol, Igor Carron, Introduction, What's New....

Lightning talk (5 minutes)

+ Jean-Baptiste Tien, Criteo, Update on the Kaggle Criteo contest ( remote lightning talk from Palo Alto)

Full Talks (15-20 minutes)

+ Maël Primet, Snips,

Machine Learning for Context-Awareness

Abstract: Your mobile phone is becoming your trusted companion & entry point for most of your activities: meeting with friends, finding a coffee shop, buying clothes, photographing your memories, or writing your thoughts. In order serve you best, your devices will now have to learn your every preferences, make sense of your context wherever you are, and predict with accuracy what you are going to do next and with who. At Snips, we use machine-learning & beautiful design to complete our mission: turning your mobile devices into a brain, in your pocket! 

+ Cédric Coussinet:  

Langage Nomo

 Le projet nomoSeed propulse le langage nomo pour concevoir des systèmes complexes temps-réel avec des capacités d'apprentissage incrémental. Le langage nomo permet de définir une base de règles toujours prêtes à réagir à tout événement et pouvant s’adapter et créer des règles en fonction des interactions constantes avec l'environnement. http://nomoseed.org

+ Philippe Duhamel & Nicolas Chollet (www.clustaar.com)

Extract Consumer Insight from Seach Engine Queries

Abstract:  150 billion searches are made in Google each month on a global basis. As an increasing number of cases indicates, analyzing the terms people search for in Google offers a new understanding of how people and consumers behave and express their needs and concerns. In this presentation, we show how algorithm-based and semantical search term analysis can bring a powerful and relevant market insights to brands and organizations. 

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