Introduction to Machine Learning: Methods and Applications

Training by William Arbour.
Wednesday, November 20, 2024, from 1:00 PM to 4:00 PM.
Hybrid format: In room C-2059, Pavillon Lionel-Groulx, Université de Montréal, and online.

Registration required only for Zoom.

In-person attendance is available without the need for registration.

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Presentation PDF

Summary:

The training will cover fundamental concepts of applied machine learning. It will include an introduction to parametric methods such as Ridge and Lasso regressions, as well as non-parametric methods like regression trees and random forests. We will also address unsupervised classification methods, using concrete examples in criminology to illustrate their application. This training is open to students of all levels. By the end of the session, students will be able to master key machine learning techniques, apply them to real-world criminology problems, and critically engage with scientific literature.

Biography:

William Arbour

Assistant Professor, Department of Economics
william.arbour@umontreal.ca

William Arbour is an Assistant Professor in the Department of Economics at the Université de Montréal. His research focuses on the determinants of criminal recidivism (behavioral therapy, parole, halfway houses), the economics of crime, applied microeconometrics, and methods from artificial intelligence. He teaches public policy evaluation at all levels, as well as data science.