Optimization for Machine Learning
M2 IASD Apprentissage, Université Paris Dauphine-PSL, 2025-2026
Aim of the course
Study the main optimization techniques used in machine learning and data science, as well as their underlying principles.
Course material (in French)
Exercises (Jan. 28 version)
PDF
Session 1: Introduction and gradient methods
Virtual board (Gradient methods)
PDF
Companion notebook (Gradient methods)
[Sources]
Session 2: Optimizers
Virtual board (Stochastic methods and optimizers)
PDF
Companion notebook (Pytorch methods)
[Sources]
Session 3: Computing derivatives
Virtual board (Exercises and differentiation)
PDF
Companion notebook (automatic differentiation)
[Sources]
Materials on this page are available under Creative Commons
CC BY-NC 4.0 license.
La version française de cette page se trouve
ici.