Statistical Learning II

Welcome to the course page for Statistical Learning II. Here you’ll find all the course information and materials.

Course Information

  • Instructors:
    • Dr. Bruno Loureiro (main instructor)
    • Leonardo Defilippis (TA)
  • Email: bruno.loureiro@di.ens.fr
  • Semester: Fall 2024
  • Class Times: Wednesdays, 08:30 AM - 11:45 AM
  • Location: Check at the Dauphine ENT.

Course Description

This course is a continuation of the “Statistical Learning I” course taught at the 2nd year (L2) of the Double Licence Intelligence Artificielle et Sciences des Organisations (IASO) undergraduate from Université Paris-Dauphine.

Our goal is to build a basic understanding of the mathematics behind some of the classical machine learning algorithms, such as:

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

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

Course Schedule

Date Lecture Topic Materials
Sept 11 - Introduction
- Recap of Linear Algebra
Slides
Sept 18 - Recap of Probability
- Supervised Learning
Slides
Sept 25 - Supervised Learning (continued) Slides
Oct 02 - Least-squares regression Slides
Oct 09 - Least-squares regression (continued) Slides
Oct 16 - Bias-variance decomposition Slides
Oct 23 Midterm exam  
Oct 30 Reading week (no class)  
Nov 06 - Ridge regression Slides
Nov 13 - Ridge regression (continued) Slides
Nov 20 - Best subset selection
- LASSO
Slides
Nov 27 - LASSO (continued) Slides
Dec 04 - PCA
- Feature maps
Slides
Dec 11 - Kernel ridge regression Slides