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Data Science Academic software: From scikit-learn and scikit-image to domain science
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Europe/Paris
Amphi Saphir (Telecom ParisTech)
Amphi Saphir
Telecom ParisTech
46 rue Barrault, 75013 Paris
Description
You work on domain science (biology, physics, chemistry, life science, etc.) and you deal with data analysis challenges? Or you are a machine learning expert curious to discover and learn the tools CDS partners contribute to build?
What you will learn:
- machine learning using Scikit-Learn http://scikit-learn.org
- image processing using Scikit-Image http://scikit-image.org
- how these tools allow to solve problems in domain sciences
- how these packages are developed by people in the CDS
- best practices for successful academic software development
It will also be a great opportunity to increase your network within the Paris-Saclay environment, discover the data challenges from other disciplines and start new collaborations.
Participants
Adel Mezine
Ahmed Gater
AKIN KAZAKCI
alain trubuil
Albert Thomas
Alessia Quatela
Alexandre Boucaud
Alexandre Gramfort
Andre Schaaff
Andrés Almansa
Antoine Bureau
Arturo Guizar
Aurélien Decelle
Balázs Kégl
Basile Mayeur
Benjamin BERTINCOURT
Boualam HASNOUN
Christopher Kermorvant
Claire Vernade
David Landriu
Djalel Benbouzid
Eric Benhaim
fabio acero
François Deslandes
François Gonard
Frédéric Vincent
Gaétan Marceau Caron
Guillaume Lecué
Guillaume TERRASSE
Hervé BALLANS
Jean Lafond
Jeanne Pigassou
Karl Kosack
LIU Gang
Lorenzo De Santis
Marc Schoenauer
Marian Douspis
mehdi cherti
Nacim BELKHIR
Nicolas Goix
Nikolaus HANSEN
Odile Bénassy
Oscar Najera Ocampo
Paul de Nazelle
Pierre Froment
Rachel Bittner
Rafael Monnerat
Romain Brault
Romane Gauriau
Sana Tfaili
Sourava Prasad Mishra
stéphane paulin
Sylvain Caillou
Sébastien Simard
Sébastien Treguer
Thomas Schmitt
Victor Estrade
Xin SU
