Data Science Academic software: From scikit-learn and scikit-image to domain science

mardi 18 nov. 2014, 13:30 → 18:00 Europe/Paris

Amphi Saphir (Telecom ParisTech)

Alexandre Gramfort (Telecom ParisTech, CNRS)

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.

 

13:30 → 15:00 Intro to the tools¶

13:30 Scikit-Learn¶

Orateur: Olivier Grisel (INRIA)

Transparents Income_classification.ipynb scikit_learn_0_15_webcast.pdf

14:15 Scikit-Image¶

Orateur: Emmanuelle Gouillart (CNRS)

Slides cds-scikit-image.pdf

15:00 → 15:30 Coffee break¶

15:30 → 16:30 Domain science use cases¶

15:30 NiLearn¶

Orateur: Dr Gael Varoquaux (INRIA)

Slides slides.pdf

15:50 Mining brain waves with MNE¶

Orateur: Alexandre Gramfort (Telecom ParisTech, CNRS)

Transparents

• demo_mne_sklearn.html
• demo_mne_sklearn.ipynb
• mne_cds_nov2014.pdf

16:10 Scikit-Learn in Particle Physics¶

Orateur: Gilles Louppe

Slides slides.pdf

16:30 → 17:00 Wrap it up¶

16:30 From flop to success in academic software development¶

Orateur: Dr Gael Varoquaux (INRIA)

Slides slides.pdf

17:00 → 18:00 Coffee break¶