Support Vector Machines and Maximizing Margins in Machine Learning - Lecture 20

Support Vector Machines and Maximizing Margins in Machine Learning - Lecture 20

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a comprehensive lecture on Support Vector Machines (SVM) that delves into the fundamental relationship between margin maximization and linear classifier learning. Understand the SVM objective function and its role in training, while discovering the concept of regularized risk minimization. Learn through detailed explanations and examples in this 81-minute machine learning lecture from the University of Utah's Data Science program. Access supplementary materials and detailed lecture notes through the provided course website to enhance understanding of this crucial machine learning algorithm.