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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
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.