Optimization Techniques in Machine Learning: A Comprehensive Review

Optimization plays a crucial role in the development and performance of machine learning models. Various optimization techniques have been developed to enhance model efficiency, accuracy, and generalization. This paper provides a comprehensive review of optimization algorithms used in machine learning, categorized into first-order, second-order, and heuristic-based methods. We discuss their advantages, limitations, and applications, highlighting recent advancements and future research directions.