Machine Learning (2023/2024)

Description

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. 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.

Teaching Staff

Slides, Notebooks and Other Material

Slides and codes developed during lectures and exercise sessions Anaconda Download

Info

Lectures

Dr. Francesco Trovò

Exercise Sessions

Stefano Samele
Vanja Miskovic