Mark Hannes Fischer: Catalogue data in Autumn Semester 2020

Name Dr. Mark Hannes Fischer
Address
Universität Zürich Physik Institut
Winterthurerstrasse 190
Y36K96
8057 Zürich
SWITZERLAND
Telephone0446354010
E-mailfismark@ethz.ch
URLhttps://www.physik.uzh.ch/en/groups/neupert/team/mfischer.html
DepartmentPhysics
RelationshipLecturer

NumberTitleECTSHoursLecturers
402-0825-00LIntroduction to Machine Learning for the Sciences
Special Students UZH must book the module PHY371 directly at UZH.
5 credits2V + 2UT. Neupert, M. H. Fischer
AbstractThis course is an introduction to the basic concepts of machine learning, including supervised and unsupervised learning with neural networks, reinforcement learning, and methods to make the learned results interpretable. The material is presented with scientific research applications in mind, where data has often very peculiar structure and quantitative accuracy is paramount.
ObjectiveThe goal is to become familiar with basic machine learning techniques for scientific applications, through lectures and practical programming exercises.
ContentMachine learning algorithms enjoy a large and increasing number of technological applications. They help us to extract relevant information from big datasets and transform the way we interact with machines. In the sciences, machine learning emerges as a more and more routinely used tool with applications in physics, geography, medicine, chemistry, biology and more. This course offers an introduction to the basic concepts, including supervised and unsupervised learning with neural networks, reinforcement learning, and methods to make the learned results interpretable. The material will be presented with scientific research applications in mind, where data has often very peculiar structure and quantitative accuracy is paramount. In the exercise class, examples will be implemented with openly available machine learning libraries.

The lecture an exercise class will be held at Y24-G-55 (Uni Zürich, Irchel Campus) and streamed as well as recorded. The recording of the lecture will be made available afterwards, but it is highly recommended to join the lecture or the live stream. Several seats outside of the field of view of the camera are available.

Lecture:
Friday 13.00-14.45, Y24-G-55 (Uni Zürich, Irchel Campus)

Exercises:
Friday 15.00-16.45, Y24-G-55 (Uni Zürich, Irchel Campus)
Lecture notesA skript will be made avialable
Prerequisites / NoticeThe course is tailored to students of the sciences with interest in numerical methods and a solid knowledge of linear algebra and calculus.