There is a wide gap between academic machine learning and industrial data science. The goal of this workshop was to bring together researchers from academia and industry to share experiences. In particular, it was an occasion to discuss which machine learning techniques are actually implemented in practical systems, as well as the open challenges that remain to be solved
Check out videos from the workshop below….
Speaker: Balázs Kégl
Learning to discover : Machine Learning in High-Energy Physics
Read more about Balázs here . Twitter: @balazskegl
Speaker: Francis Bach
Beyond stochastic gradient descent: From theory to practical
Read more about Francis here .
Speaker: Guillaume Bouchard
Factorizing rational databases
Read more about Guillaume here . Twiiter: @gbouchar
Speaker: Christopher Kermorvant
Handwritten text recognition: Is it a solved problem?
Read more about Christopher here.
Speaker: Nicolas Le Roux
Scientific challenges at Criteo
Read more about Nicolas here.
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