Statistical learning 2

Crédit : 4 ECTS
Langue du cours : anglais

Volume horaire

• CM : 39 h
• Volume horaire global (hors stage) : 39 h

Compétences à acquérir

The goal of this course is to get acquainted with the mathematics behind the classical machine learning algorithms.

Description du contenu de l'enseignement

We will cover the following topics in this course:

• Least squares regression
• Ridge regression
• LASSO
• PCA
• Kernel methods

Mode de contrôle des connaissances

• 25% Midterm exam
• 75% Final exam

Pré-requis obligatoires

• Linear algebra
• Basic probability

Bibliographie, lectures recommandées

The material in this course takes inspiration from the following excellent ressources:

• Bach, Francis. Learning theory from first principles. MIT press, 2024.
• Hastie, Trevor, et al. The elements of statistical learning: data mining, inference, and prediction. Vol. 2. New York: springer, 2009.
• Murphy, Kevin P. Machine learning: a probabilistic perspective. MIT press, 2012.
• Wasserman, Larry. All of statistics: a concise course in statistical inference. Springer Science & Business Media, 2013.

Enseignant responsable

BRUNO LOUREIRO