Statistical learning 2

ECTS : 4

Lecturer in charge : Bruno LOUREIRO (https://brloureiro.github.io/)

Language of instruction : French

Teaching hours : 39

Course content:

We will cover the following topics in this course:

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

Skills to be acquired:

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

Mandatory prerequisites

• Linear algebra
• Basic probability

Assessment:

• 25% Midterm exam
• 75% Final exam

Bibliography, recommended reading:

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.