Fernando Perez Cruz: Catalogue data in Spring Semester 2020

Name Prof. Dr. Fernando Perez Cruz
Swiss Data Science Center (SDSC)
ETH Zürich, TUR E 21
Turnerstrasse 1
8092 Zürich
DepartmentComputer Science
RelationshipAdjunct Professor

263-5225-00LAdvanced Topics in Machine Learning and Data Science Restricted registration - show details
Number of participants limited to 20.

The deadline for deregistering expires at the end of the fourth week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
2 credits2SF. Perez Cruz
AbstractIn this seminar, recent papers of the machine learning and data science literature are presented and discussed. Possible topics cover statistical models, machine learning algorithms and its applications.
ObjectiveThe seminar “Advanced Topics in Machine Learning and Data Science” familiarizes students with recent developments in machine learning and data science. Recently published articles, as well as influential papers, have to be presented and critically reviewed. The students will learn how to structure a scientific presentation, which covers the motivation, key ideas and main results of a scientific paper. An important goal of the seminar presentation is to summarize the essential ideas of the paper in sufficient depth for the audience to be able to follow its main conclusion, especially why the article is (or is not) worth attention. The presentation style will play an important role and should reach the level of professional scientific presentations.
ContentThe seminar will cover a number of recent papers which have emerged as important contributions to the machine learning and data science literatures. The topics will vary from year to year but they are centered on methodological issues in machine learning and its application, not only to text or images, but other scientific
domains like medicine, climate or physics.
LiteratureThe papers will be presented in the first session of the seminar.
266-0100-00LCapstone Project Restricted registration - show details
Only for DAS in Data Science.
8 credits17AF. Perez Cruz, O. Verscheure, T. Hofmann
AbstractThe capstone project is part of the DAS in Data Science and is an opportunity to apply the knowledge acquired in the program in an independent, real-world project.
ObjectiveTo apply the knowledge acquired in the program in an independent, real-world project.
ContentThe capstone project can be done under the supervision of the Swiss Data Science Center, or of any core or adjunct faculty of Data Science.

The project has to be finished within 6 months.
Deadline for a project the following semester conducted at the SDSC is mid June/mid December.