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KKT Conditions
Machine Learning Mathematical Derivations (8): Support Vector Machines
Complete SVM derivation from maximum margin to Lagrangian duality, KKT conditions, soft margin, kernel trick, and SMO algorithm with step-by-step proofs and Python code.
ML Math Derivations (4): Convex Optimization Theory
Nearly every ML algorithm is an optimization problem. This article derives convex sets, convex functions, gradient descent, Newton's method, KKT conditions, and ADMM -- the optimization toolkit for machine learning.