Learn about support vector machines in this comprehensive lecture that explores the fundamental connection between maximizing margins and learning linear classifiers. Discover how the SVM objective function serves as a training tool and gain insights into regularized risk minimization. Delve into the mathematical foundations and practical applications of SVMs while understanding their role in modern machine learning classification tasks. Access supplementary materials and detailed lecture notes through the provided course website to reinforce learning concepts and theoretical frameworks presented during this 76-minute session.