# 183.584 Statistical Pattern Recognition This course is in all assigned curricula part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_20",{id:"j_id_20",showEffect:"fade",hideEffect:"fade",target:"isAllSteop"});});This course is in at least 1 assigned curriculum part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_22",{id:"j_id_22",showEffect:"fade",hideEffect:"fade",target:"isAnySteop"});}); 2021W 2020W 2019W 2018W 2017W 2016W 2015W 2014W 2013W 2012W 2011W

2021W, UE, 2.0h, 3.0EC

## Properties

• Semester hours: 2.0
• Credits: 3.0
• Type: UE Exercise
• Format: Distance Learning

## Learning outcomes

After successful completion of the course, students are able to apply fundamental theoretical principles of statistics and pattern recognition to pattern recognition problems and to implement simple pattern recognition algorithms.

## Subject of course

Implementation and evaluation of several simple classifiers

## Teaching methods

Groups of 3 students solve 3 exercises and document their findings.

Immanent

## Examination modalities

For each exercise, their will be an interview where the whole group has to defend their findings.

## Course registration

Begin End Deregistration end
07.10.2021 00:00 26.10.2021 23:59 26.10.2021 23:59

## Group Registration

GroupRegistration FromTo
Gruppe 105.10.2021 08:0014.10.2021 22:00
Gruppe 205.10.2021 08:0014.10.2021 22:00
Gruppe 305.10.2021 08:0014.10.2021 22:00
Gruppe 405.10.2021 08:0014.10.2021 22:00
Gruppe 505.10.2021 08:0014.10.2021 22:00

## Literature

No lecture notes are available.

## Previous knowledge

Der vorhergehende Besuch einer Statistik-Vorlesung wird empfohlen, ebenso der Besuch der begleitenden Vorlesung. Grundkenntnisse in linearer Algebra (Invertierbarkeit, Rang, lineare Unabhängigkeit) sind von Vorteil.

German