The Dataiku AI Lab team discusses the hottest topics in ML research with industry experts in this webinar series.

Hear from Jun Kim from Inria and Léo Grinsztajn and Gaël Varoquaux from the SODA team as they discuss their research of trying to apply Transformer recipes to tabular representation and tabular data.

In this edition of ML Research, In Practice with Dataiku's AI Lab, guest Naver Labs comes to explain the work they're doing and to dive into their recent paper on predicting performance drop under domain shift.

Andrea Castellani, Ph.D student from Bielefeld University in collaboration with Honda, joins the Dataiku AI Lab's ML Research, In Practice series to go in-depth on Industry 4.0 and digital twins.

Hear from David Stutz of DeepMind on learning optimal conformal classifiers as a part of the Dataiku AI Lab series, ML Research, In Practice.

Nicolas Woloszko of the OECD Economics Department & NAEC Innovation Lab walks through predicting gross domestic product (GDP) with Google Trends

For the past five years, Michelin has been working on incorporating more machine learning into its processes for tire design and testing.

Any artificial intelligence system deployed in the real world faces the problem of data distributional shift over time.

With the advent of the Anthropocene era, the physical territory is subject to dramatic transformations and ecological degradations due to human action.

Hear from Paolo Papotti, Associate Professor in the Data Science department at EURECOM, about how SQL and LLMs work separately and how to get the most value by using them together.