Learn how to optimize Support Vector Machine (SVM) objectives through stochastic gradient descent in this 20-minute lecture from the University of Utah Data Science program. Explore practical implementation techniques and mathematical foundations for applying SGD specifically to SVM problems, gaining essential knowledge for efficient machine learning model training.
Stochastic Gradient Descent for Support Vector Machines - Lecture 21B
Overview
Syllabus
Machine learning: Lecture 21b: Stochastic Gradient Descent for SVMs
Taught by
UofU Data Science
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