Machine Learning
A.Y. 2025/2026
Learning objectives
The objective of the Machine Learning course is to give an in depth presentation of the techniques most used for pattern recognition, knowledge discovery, and data analysis/modeling. These techniques are presented both from a theoretical (i.e., statistics and information theory) perspective and a practical one (i.e., coding examples) through the descriptions of algorithms and their implementations in general purpose programming languages.
Expected learning outcomes
At the end of this class , the students are expected to: be familiar with the most widely used techniques for pattern recognition, knowledge discovery, and data analysis/modeling; be able to write simple programs or scripts implementing them; apply them to the bionformatic analysis of biological data.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
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
Lesson period
Second semester
INF/01 - INFORMATICS - University credits: 1
ING-INF/05 - INFORMATION PROCESSING SYSTEMS - University credits: 5
ING-INF/05 - INFORMATION PROCESSING SYSTEMS - University credits: 5
Practicals: 24 hours
Lectures: 36 hours
Lectures: 36 hours
Professor:
Trovo' Francesco