Dual Formulation in SVMs isn’t just a rewrite—it’s a revolution. It shifts the optimization game from weight space to α-space, focusing only on support vectors. We unpack how dual SVMs compute smarter, enable kernel tricks, and efficiently solve non-linear problems. This post breaks it all down—from dot products to RBFs—with clarity, code, and geometric insight.