Data mining and machine learning

Coordinators : Stéphanie Durand and Thomas Bodin
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Research topics:

  • Data Science
  • Machine Learning
  • Artificial intelligence
Exploration de données et apprentissage automatique - LGLTPE

Description : 

Many of the laboratory’s research themes are based on large digital datasets, which are often composite and heterogeneous. Data mining and machine learning bring together a vast array of algorithms and techniques from disciplines such as statistics, computer science and artificial intelligence. These are powerful new tools available today for the earth sciences.

The geosciences are inherently multidisciplinary. The scientific disciplines are varied (physics, chemistry, biology) but the data analysis problems are often identical (regression, classification, detection, prediction, inversion). In this context, we have set up a cross-disciplinary research theme within the laboratory, to which each researcher is free to contribute.

The idea is to enable discussions between different themes that are often compartmentalised, but which share the same issues. We run informal discussion workshops on data mining. These take the form of monthly seminars and meetings, where we present our current projects and invite specialist researchers from outside the laboratory.