phy694 - Machine Learning II (Veranstaltungsübersicht)

phy694 - Machine Learning II (Veranstaltungsübersicht)

Institut für Physik 6 KP
Semesterveranstaltungen Sommersemester 2018
Lehrveranstaltungsform: Vorlesung
Hinweise zum Modul
Teilnahmevoraussetzungen
Basic knowledge in higher Mathematics taught as part of first degrees in Physics, Mathematics, Statistics, Engineering or Computer Science (basic linear algebra and analysis) is required. Additionally, programming skills are required (Matlab or python).
Prüfungsleistung Modul
written exam (max. 3 hours) or 30 minutes oral exam
Kompetenzziele
The students will deepen their knowledge on mathematical models of data and sensory signals. Building upon the previously acquired Machine Learning models and methods, the students will be lead closer to current research topics and will learn about models that currently represent the state-of-the-art. Based on these models, the students will be exposed to the typical theoretical and practical challenges in the development of current Machine Learning algorithms. Typical challenges are analytical and computational
intractabilities, or local optima problems. Based on concrete examples, the students will learn how to address such problems. Applications to di erent data will teach skills to use the appropriate model for a desired task and the ability to interpret an algorithm's result as well as ways for further improvements. Furthermore, the students will learn interpretations of biological and arti cial intelligence based on state-of-the-art Machine Learning models.