Latest
2025.11.10: Resources session 3, exercise sheet 2 and solutions sheet 1.
2025.11.04: Solutions for notebook+minor fix original notebook.
2025.11.03: Notebook for lecture 2.
2025.09.29: Resources from lecture 1 (board+minor change exercise 1 sheet).
2025.09.28: Course webpage online.
Instructors
Clément Royer
clement.royer@lamsade.dauphine.fr
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Optimization for Data Science
M2 MIAGE ID/ID Apprentissage, Université Paris Dauphine-PSL, 2025-2026
Aim of the course
Provide modern algorithmic tools for data science problems.
Course material
Lecture notes (Sep. 29)
PDF
Session 1: Basics of optimization
Virtual board
Session 2: Gradient methods (practice)
Notebook: introduction to gradient descent (without solutions)
Notebook: introduction to gradient descent (with solutions)
Session 3: Gradient methods (theory)
Virtual board
Illustration notebook (accelerated methods, nonconvex problems)
Tutorial resources
Tutorial 1 (basics on optimization, with solutions)
PDF
Tutorial 2 (gradient descent)
PDF
Materials on this page are available under Creative Commons
CC BY-NC 4.0
license.
La version française de cette page se trouve
ici
.