Ce soir: Paris Machine Learning #7 Season 4 @ Algolia, deep reinforcement learning, feature engineering

Tonight we will have a regular Paris Machine Learning meetup, it is #7 of Season 4 will take place @ Algolia, we will talk Deep Reinforcement Learning and Feature engineering and more....

The following video was taken by the folks at Algolia

Merci à Algolia de nous accueillir et de nous offrir le buffet de ce meetup.
Horaires :

• Ouverture des portes : 18:45 ; Début meetup : 19:00
• Présentations : 19:00-21:00 ; Network : 21:00-22:00

Au programme :

Presentation eclair: dotai.io Slides

Pitch éclair : Zineb Lamrani, Set-up start tech and mode 

Je suis en cours de développement d'une application en machine learning dans le secteur de la mode. Je suis à la recherche de plusieurs associés motivés ayant des compétences en machine learning, deep learning ... intéressés par fonder une start up tech aux service de la mode et de la beauté.

Katja Hofmann, Project Malmo: Turning Minecraft into a testbed for the future of AI, Microsoft Research Cambridge. Site: Project Malmo
Project Malmo video: https://youtu.be/KkVj_ddseO8

The idea of building machines that think and behave like people has captured people's imagination for centuries. But what is it really that makes us intelligent? What makes us, humans, intelligent, and what does this tell us about the kinds of machines that would need to be built in order to achieve artificial intelligence (AI)?

In this talk I briefly summarize the current state-of-the-art in AI - especially the fantastic progress that has been made especially in artificial perception. I then turn to the next challenge: interactive learning, and examine the progress that has been made so far. Finally, you will learn why current video games, like the popular video game Minecraft, may be key to solving the next big challenge in AI.

Video link

Thomas Seleck, Features engineering by a Kaggle Expert
HTML link

L'objectif de cette présentation est de présenter les différents types de feature engineering et leur application à des données réelles. Talk + code

Jean-Baptiste Priez, Données relationnelles et Feature Engineering, Predicsis

Pourquoi réfléchir à quelles données remonter/agréger quand la machine peut le faire pour vous ? Talk + code

Edmund Ronald, Get your paper accepted

Yaël Frégier, Internship offer ( https://sites.google.com/site/homepagelml/ )

Generative adversarial networks for forged signature detection and black and white photos colorization everything is in the title!

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