Support Vector Machine 3.11 - SVM Summary/ClipID:44092 previous clip next clip

Recording date 2022-10-16

Course

Machine Learning for Engineers I

Lecturer

Prof. Dr. Björn Eskofier

Via

Studon

Language

English

Organisational Unit

Lehrstuhl für Maschinelles Lernen und Datenanalytik

Producer

Friedrich-Alexander-Universität Erlangen-Nürnberg

Format

lecture

Type

university lecture

Up next in Chapter

Principal Component Analysis 4.1 - Intuition
Eskofier, Björn
Prof. Dr. Björn Eskofier
2022-10-16
Studon
Principal Component Analysis 4.2 - Mathematics 1
Eskofier, Björn
Prof. Dr. Björn Eskofier
2022-10-16
Studon
Principal Component Analysis 4.3 - Mathematics 2
Eskofier, Björn
Prof. Dr. Björn Eskofier
2022-10-16
Studon
Principal Component Analysis 4.4 - Applications
Eskofier, Björn
Prof. Dr. Björn Eskofier
2022-10-16
Studon
Principal Component Analysis 4.5 - Summary
Eskofier, Björn
Prof. Dr. Björn Eskofier
2022-10-16
Studon

More clips in this category "Technische Fakultät"

12 - Übung Halbleitertechnik II - CMOS Technik (HL II) - Übungsblatt 7 aus WS2023/24 - Teil 1
2025-02-05
IdM-login
protected  
40 - Vorlesungen und Übungen zu Maschinenelemente I
2025-02-04
Studon
protected  
29 - Artificial Intelligence I
2025-02-05
Free
public  
29 - Grundlagen der Elektrotechnik I
2025-02-04
IdM-login
protected  
17 - Lecture 16 - Computational Fluid Dynamics 1 (CFD1)
2025-02-04
IdM-login
protected  
28 - Algorithmen und Datenstrukturen (für Medizintechnik)
2025-02-04
Studon
protected