The course offers an introduction to the mathematical theory of machine learning, whose tools are at the basis of modern machine learning algorithms and large data analysis. The course is aimed at master students in Mathematics, but it can also be followed by students in SMID.
The primary objective is to provide the students with the basic language and tools of machine learning, with particular emphasis on the supervised case. The approach is based on a formulation of the problem of machine learning as an inverse stochastic problem. The students will also need to know some of the best known algorithms, including both statistical and computational properties.
At the end of the course, the student will have:
Calculus 1 and 2, probability and linear algebra.
Classes using blackboard
Ricevimento: Friday 14-16
Ricevimento: By appointment wich can be fixed in person or via email : villa@dima.unige.it
ERNESTO DE VITO (President)
LORENZO ROSASCO (President)
SILVIA VILLA
In agreement with the offical academic calendar
To pass the exam the student have to write and present a short report (max 10 pages). The student can choose one among the following options:
The topic studied in the report must be decided in advance in agreement with the teachers. The length and the difficulty of the thesis will be different depending whether the course is of 6 or 7 CFUs.
The report preparation and its discussion are aimed at verifying the student's achievement of an independent critical reasoning capability in the context of machine learning.
In addition, the report writing will be used to assess the student's ability to elaborate in written form his ideas.
The wide range of possible topics allows to adapt the requested skills to students of the Bachelor and the Master degree,