Chapter 25. Learning from Observations 7.18 - 25.9. Support Vector Machines/ClipID:30386 previous clip next clip

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Recording date 2021-03-30
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Course

Artificial Intelligence (AI-2) SS 2021

Lecturer

Prof. Dr. Michael Kohlhase

Via

Free

Language

English

Organisational Unit

Professur für Wissensrepräsentation und -verarbeitung

Producer

Friedrich-Alexander-Universität Erlangen-Nürnberg

Format

lecture

Type

university lecture

Definition of Support Vector Machines and how to find the Maximum Margin Separator. The Kernel Trick is explained for cases where the data is not linearly separable. Also, there is a short summary for this chapter. 

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