Machine Learning (ML) enables computers to address problems by learning from data. Over the last years, its abilities have increasingly been applied to a wide variety of chemical challenges, from improving computational chemistry to drug and materials design and even synthesis planning [1-2]. “ML meets chemistry” is a one-day event with the purpose of introducing this fast growing reality to students, researchers and professors of the department of chemistry of the university of Turin. In order to do so, we invited several experts to talk about ML applied to chemical problems through informative and basic level lectures. “ML meets chemistry” event belongs to the PhD Programme in Chemical and Materials Sciences of the Doctoral School of the University of Torino. Due to its informative nature, attending to this event is free of charge, but registration is mandatory. Here you can find the program of the event.
The organizing committee, Prof. Piero Ugliengo and Dr. Michele Cutini
[1] How to explore chemical space using algorithms and automation Nature Reviews Chemistry 2019, 3, 119–128
[2] Deep Learning in Chemistry J. Chem. Inf. Model. 2019, 59, 2545-2559