ADVANCES IN MACHINE LEARNING: A SURVEY OF METHODS, MODELS, BENCHMARKS, AND INDUSTRY APPLICATIONS

Abstract

This study examines the fundamentals of Machine Learning (ML), a key branch of Artificial Intelligence (AI) that enables systems to learn and adapt from data without explicit programming. It outlines core ML types and approaches, emphasizing their ability to improve with experience. The paper also traces ML’s evolution—from statistical learning theory to modern neural networks—highlighting how big data and computational advances have accelerated its growth. Finally, the study explores ML applications across sectors such as healthcare, finance, and retail, showcasing its role in solving complex problems, enhancing decision-making, and driving industry transformation.