Support Vector Machines: Maximising the Margin

How an SVM finds the widest-margin boundary between two classes, the kernel trick that lets it draw curved boundaries without computing a higher-dimensional space directly, and a runnable RBF-kernel example.

~5 min total·4 quadrants of structured content

By the end of this topic, you will

Explain what a support vector is and why only points near the boundary matter to an SVM
Explain what the kernel trick lets an SVM do that a plain linear boundary cannot
Train an RBF-kernel SVC in scikit-learn

Quadrant 1 · e-Tutorial

Video lectures and walkthroughs

Video content coming soon.

Quadrant 2 · e-Content

Articles and case studies

Support Vector Machines: Maximising the Margin

Where a tree asks a sequence of axis-aligned questions, a support vector machine looks for the single boundary that separates two classes with the widest possible margin.

Quadrant 3 · Web Resources