“Machine Learning in Experimental Sciences”: an event by Graduate School Chemistry and the diiP

The objective of this event is to provide Master’s and PhD students with an overview of popular Machine Learning (ML) methods developed, and their use in the main experimental research fields such as biology, physics, health, the environment, etc. The ambition is to present the tools and their uses for the analysis of data classically encountered in science (image analysis, statistical data, etc.), so that students understand the benefits, as well as limitations, of the methods, incorporate them in their work, and develop collaborations with specialists in the data analysis field.