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Challenge Data 2016-2017

21/10/2016 - 01/01/2018

Challenge Data 2018

16/11/2017 - 27/12/2018
Challenge Data 2016-2017

21/10/2016 - 01/01/2018
Challenge Data 2015-2016

21/10/2015 - 01/07/2016

Cluster actor faces from TV show — Cluster actor faces from TV show
In this challenge, we provide you with faces extracted from 20 episodes of a TV show. The goal is to gather, for each movie, all the faces that belong to the same actor into homogeneous and complete c

Prediction of products reviews interests — Prediction of products reviews interests
PriceMinister is one of the leading marketplace of E-commerce in France, and is part of the Rakuten group, leader in Japanese market. The goal of this challenge is to predict if a review of a user

Predict the Crude Oil production trend. — Predict the Crude Oil production trend.
Predict the Crude Oil production's trend base on the previous year Crude Oil data.

Prediction of trading activity within the order book — Prediction of trading activity within the order book
With past order book snapshots, try to predict if any trading activity will happen within the next second.

Failure risk prediction on pipeline network — Failure risk prediction on pipeline network
The goal of this challenge is to predict which pipes have the highest failure risk in the two next years.

Post Recommendation in a Collaborative Platform — Post Recommendation in a Collaborative Platform
The goal of the challenge is to build a recommender system for the social and collaborative application that is integrated within the 3DEXPERIENCE Platform (Dassault Systèmes). For each user, this sy

Age prediction from EEG signals — Age prediction from EEG signals
The goal of this challenge is to predict the age of subject from his brain activity during deep sleep and the sequence of his sleep stages over a night.

Oze Energies : Optimizing energy consumptions — Oze Energies : Optimizing energy consumptions
This data challenge aims at introducing a new statistical model to analyze energy consumptions in several buildings using observations received from sensors. These observations are decomposed into: -

Predict which clients reduced their consumption — Predict which clients reduced their consumption
EDF is constantly seeking to improve customer experience, notably in helping its customers to better understand and thus better manage their energy consumption.

Predict air quality at the street level — Predict air quality at the street level
We propose to predict the air quality level at the street level in several French cities. To reach this goal, we rely on an increasingly popular kind of model in the atmospheric science community call

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