ENSAE Alumni Data Science Meeting

Machine learning vs. statistics: what's the difference for professionals?

ENSAE Alumni invites you to take part in the fourth edition of their new series of events:

ENSAE Alumni Data Science Rendezvous

Machine learning vs. statistics,

what are the differences for professionals?

Friday November 21st at 8.15am

in the Salon Venise of the Hôtel Castille

33, rue Cambon, 75001 Paris

To discuss the various issues involved, a specialist will share his views and answer your questions:

Gilbert Saporta (Professor Emeritus, Applied Statistics, Conservatoire National des Arts et Métiers)

Stéphan Clémençon ( Head of the "Big Data" Specialized Master's program, Télécom ParisTech)

Despite the general excitement surrounding it, the emergence of the data scientist profession is not always perceived by statisticians and econometricians as an opportunity - quite the contrary.

At the heart of the debate are two different approaches, two different cultures, two different styles: on the one hand, machine learning, which stems from artificial intelligence and information science research, is geared towards predictive performance; on the other, classical statistics, often perceived as more theoretical, is more focused on fundamental explanation.

But are these approaches really so different scientifically? How do they find their respective applications in day-to-day business projects? And how do you move from one to the other? And isn't the synthesis of the two the very essence of data science?

To discuss these issues, Gilbert Saporta and Stephan Clémençon will share their points of view and answer your questions.