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
Recommended literature
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.
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 |