The goal of the course is to discuss automatic methods to make predictions and build models starting from available data. The course will teach the student the theoretical bases of machine learning (fundamentals of statistical learning theory, classification, regression) and common methods for typical tasks (e.g., clustering and dimensional reduction).
Expected learning outcomes
The student will be able to analyse data choosing the most appropriate method among well-established ones. Moreover, they will be familiar with the notions and the language which is common to the disciplines that employ such methods (e.g., computer science, economy, mathematics).
Lesson period: First semester
(In case of multiple editions, please check the period, as it may vary)