ML-s2-2025
Machine Learning @Sapienza
Course material, 2nd semester a.y. 2024/2025, Mathematical Sciences for AI (SMIA)
News 🗞️
- 12/04/2025: No lecture on April 21-22 due to Easter holidays.
- 06/04/2025: The theoretical lecture of April 07 is cancelled by Sapienza. Please watch the recorded video lectures as a replacement, links can be found below.
- 07/02/2025: The course website is online. Welcome to ML 2024/25! The course will start on Mon 3rd March.
Logistics 🧭
Lecturer: Prof. Emanuele Rodolà (rodola@di.uniroma1.it)
Assistants: Dr. Daniele Solombrino (solombrino@di.uniroma1.it)
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 🔑
Python fundamentals; calculus; linear algebra.
Textbook and reading material 📖
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 📊
Exam dates
- 23 June 2025
- 15 July 2025
- 04 September 2025
- 16 September 2025
- 23 January 2026
Evaluation proceeds according to the following steps:
- A project (mandatory, accounts for 100% of the final grade).
- An oral exam (optional, grants from -3 to +3 points to the final grade).
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 📑
Exam is now project-only, but you can still find some past theoretical questions here
Lectures 🗣️
| Date | Topic | Reading | Code & Data |
|---|---|---|---|
| Mon 3 Mar | 🌐 Introduction; Talking sense about data I | slides | |
| Tue 4 Mar | 🔢 Talking sense about data II; Linear algebra revisited; Introduction to Python notebooks and NumPy | slides ; linear algebra recap ; matrix notes | |
| Mon 10 Mar | 🀠 Array manipulation |  |
|
| Tue 11 Mar | 📏 Regression problems | slides ; matrix gradient notes | |
| Mon 17 Mar | 📏 Linear regression and scikit-learn | 🐱 |
|
| Tue 18 Mar | 📉 Regularization; Stochastic gradient descent | slides 1 ; slides 2 | |
| Mon 24 Mar | 📉 Stochastic gradient descent | |
|
| Tue 25 Mar | 🔁 Multi-layer perceptron and back-propagation | slides | |
| Mon 31 Mar | 🔥 PyTorch and Deep Learning I | |
|
| Tue 01 Apr | 🔥 PyTorch and Deep Learning II | use yesterday’s notebook | |
| Mon 07 Apr | 👻 PCA, spectra, and low-rank approximations | slides video SVD video PCA | |
| Tue 08 Apr | 👻 Principal Component Analysis | 🦒 😀 |
|
| Mon 14 Apr | 🚀 Hackathon | 🙋 🐉 |
|
| Tue 15 Apr | 🚀 Hackathon | |
|
| Mon 21 Apr | 🐇 Easter holidays | ||
| Tue 22 Apr | 🐇 Easter holidays | ||
| Mon 28 Apr | 🗺️ Manifold learning and dimensionality reduction | upcoming | |
| Tue 29 Apr | 🗺️ MDS and t-SNE | upcoming |
