VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.

103-0849-00L 4 Credits BSC D-BAUG

Multivariate Statistics and Machine Learning

Multivariate Statistik und Machine Learning

Lecturers & Examiners: Prof. Dr. Konrad Schindler
VVZ CR n/a

Last Updated: 2026-06-04 00:25:06

Abstract

Introduction to statistical modelling and machine learning.

Objective

The goal is to familiarise students with the principles and tools of machine learning, and to enable them to apply them for practical data analysis.

Content

multivariate probability distributions; comparison of distributions; regression; classification; model selection and cross-validation; clustering and density estimation; mixture models; neural networks

Resources

Literature

C. Bishop: Pattern Recognition and Machine Learning, Springer 2006 T. Hastie, R. Tibshirani, J. Friedman, The Elements of Statistical Learning, Springer 2017 R. Duda, P. Hart, D. Stork: Pattern Classification, Wiley 2000

General Information

Language
German
Levels
BSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 90 minutes
Aids
- Ein beschriebenes A4-Blatt (Vorder- und Rückseite), Handschrift oder 11pt Font- Unbeschriebenes Papier, Stift- Taschenrechner wird am Desktop zur Verfügung gestellt
Digital
The exam takes place on devices provided by ETH Zurich.

Registration & Places

Priority: Registration for the course unit is only possible for the primary target group

Course Components

Type Title Time & Place Hours
lecture with exercise Multivariate Statistik und Machine Learning
  • Thu 08:45-11:30 (HPV G 5)
3 h weekly

Offered In