Lecture

Support Vector Machines: SVM Basics

In course

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Description

This lecture covers the basics of Support Vector Machines (SVM), focusing on the hard-margin and soft-margin formulations. It explains the concepts of separating hyperplanes, margins, support vectors, and the optimization problems involved in SVM. The lecture also discusses the role of slack variables in handling non-linearly separable data and the importance of regularization in SVM algorithms.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_jwxmmw6s

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Ontological neighbourhood

Theoretical computer science

Algorithms and data structures: Combinatorial optimization

Statistics

Statistical inference: Mathematical statistics

Industrial and production engineering

Industrial processes: Machine tool

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