Machine Learning and Statistical Learning

A.Y. 2024/2025
12
Max ECTS
80
Overall hours
SSD
INF/01 SECS-S/01
Language
English
Learning objectives
The course introduces students to the most important algorithmical and statistical machine learning tools. The first part of the course focuses on the statistical foundations and on the methodological aspects. The second part is more hands-on, with laboratories to help students develop their software skills.
Expected learning outcomes
Upon completion of the course students will be able to:
1. understand the notion of overfitting and its role in controlling the statistical risk
2. describe some of the most important machine learning algorithms and explain how they avoid overfitting
3. run machine learning experiments using the correct statistical methodology
4. provide statistical interpretations of the results.
Single course

This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.

Course syllabus and organization

Single session

Responsible
Lesson period
Second semester
Course syllabus
The syllabus is shared with the following courses:
- [F94-155](https://www.unimi.it/en/ugov/of/af2025000f94-155)
Machine Learning and Statistical Learning-Module Machine Learning
INF/01 - INFORMATICS - University credits: 6
Lessons: 40 hours
Machine Learning and Statistical Learning-Module Statistical Learning
SECS-S/01 - STATISTICS - University credits: 6
Lessons: 40 hours
Professor: Salini Silvia
Professor(s)
Reception:
Wednesday 9:30AM-12:30PM
18, via Celoria. Room 7007
Reception:
The student reception is in attendance, by appointment, on Tuesday from 09.30 to 11.00 and via Teams, by appointment, on Monday from 15.00 to 16.30.
DEMM, room 30, 3° floor