Professional Development · IT & Digital · Module 3: More Algorithms

Support Vector Machines (SVM)

4 Abschnitte1 Karteikarten-Decks1 Quizze

Understand SVMs — how they find the optimal decision boundary by maximising the margin between classes, and how kernel functions handle non-linear problems.

Inhaltsübersicht

  • The Maximum Margin Classifier
  • Support Vectors, Soft Margin, and the C Parameter
  • The Kernel Trick: Non-Linear Decision Boundaries
  • SVM in Practice: Strengths, Limitations, and scikit-learn
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Learn Support Vector Machines (SVM) — Machine Learning — From Theory to Practice IT & Digital | Summary, Flashcards & Quiz