227-0105-00L  Introduction to Estimation and Machine Learning

SemesterHerbstsemester 2020
DozierendeH.‑A. Loeliger
Periodizitätjährlich wiederkehrende Veranstaltung

KurzbeschreibungMathematical basics of estimation and machine learning, with a view towards applications in signal processing.
LernzielStudents master the basic mathematical concepts and algorithms of estimation and machine learning.
InhaltReview of probability theory;
basics of statistical estimation;
least squares and linear learning;
Hilbert spaces;
Gaussian random variables;
singular-value decomposition;
kernel methods, neural networks, and more
SkriptLecture notes will be handed out as the course progresses.
Voraussetzungen / Besonderessolid basics in linear algebra and probability theory