Optimization#
At the heart of ML is optimization: the process of adjusting parameters so models learn effectively. This chapter explores optimization as a general discipline—finding minima, balancing constraints, and navigating high-dimensional landscapes. Beyond ML, these methods apply to scheduling, logistics, resource allocation, and scientific modeling.