ML-s2-2025

Machine Learning @Sapienza

Course material, 2nd semester a.y. 2024/2025, Mathematical Sciences for AI (SMIA)

News πŸ—žοΈ

Logistics 🧭

Lecturer: Prof. Emanuele RodolΓ 

Assistants: Dr. Daniele Solombrino

When: Mondays 10:00–13:00 and Tuesdays 8:00–11:00

Where:

Aula Picone - Piano Terra, Dip. di Matematica Castelnuovo (CU006-E01PTEL008)

There is no virtual classroom, and the lectures will not be recorded.

Pre-requisites πŸ”‘

Python fundamentals; calculus; linear algebra.

Textbook and reading material πŸ“–

Due to the continuously evolving nature of the topic, there is no fixed textbook as a reference. Specific material in the form of slides, course notes, notebooks, scientific articles, and book chapters will be given throughout the lectures.

Grading πŸ“Š

Exam dates

Evaluation proceeds according to the following steps:

There will also be a midterm self-evaluation test; it is optional, and does not concur to the final grade.

We may require an oral exam in doubtful cases or whenever necessary.

Past exams πŸ“‘

Exam is now project-only, but you can still find some past theoretical questions here

Lectures πŸ—£οΈ

Date Topic Reading Code & Data
Mon 3 Mar 🌐 Introduction; Talking sense about data I slides  
Tue 4 Mar πŸ”’ Talking sense about data II; Linear algebra revisited; Introduction to Python notebooks and NumPy slides ; linear algebra recap ; matrix notes Β