Mathematics of machine learning

Mathematics of machine learning

Semester
WiSe 2023 / 24

Lecturer
Hoang Kim Nguyen, Florian Strunk

Type of course (Veranstaltungsart)
Vorlesung

Contents
This course aims to discuss mathematical foundations of machine learning. Possible topics will
include probability theory and statistics, information theory as well as optimization. As
applications we will discuss classification of data sets and generative ai. The course will first
start as lecture on the necessary mathematical topics. Once we have built a solid base, our goal is
to develop theory and application in parallel, in particular we will aim to implement the theory in
practice.

Literature
tba

Recommended previous knowledge
Linear Algebra I and II, Basic probability theory

Time/Date
Tuesday 10-12

Location
M103 (Tuesday)

Course homepage
https://elearning.uni-regensburg.de/course/view.php?id=63787
(Disclaimer: Dieser Link wurde automatisch erzeugt und ist evtl. extern)

Registration

Registration for course work/examination/ECTS: FlexNow

Course work (Studienleistungen)

Oral examination (without grade): Duration: 30, Date: individually

Examination (Prüfungsleistungen)

Oral exam: Duration: 30, Date: individually, re-exam: Date: individually

Modules
MV

ECTS
3