Explore a 15-minute lecture that delves into the fundamental concept of framing machine learning as an optimization problem, focusing specifically on loss minimization and empirical risk minimization. Build upon previous learning concepts to understand how machine learning problems can be declaratively expressed through the lens of risk minimization, providing a mathematical framework for understanding learning algorithms.