Machine Learning: A Comprehensive Review of Algorithms, Applications, and Emerging Frontiers
DOI:
https://doi.org/10.66069/ojspub.26820802Keywords:
machine learning, algorithms, applications, deep learning, research trends, reviewAbstract
As a cornerstone technology of artificial intelligence, machine learning (ML) has witnessed rapid advances in recent years. This study presents a systematic review of the ML landscape, tracing its historical evolution, critically examining classical algorithms (e.g., supervised, unsupervised, and reinforcement learning), and surveying the latest research frontiers, including deep learning and transfer learning. The review further synthesizes ML applications across diverse domains—from healthcare and finance to autonomous systems—and discusses emerging challenges such as interpretability, data privacy, and computational efficiency. Finally, the paper outlines promising future research directions, aiming to provide a comprehensive reference for both newcomers and experienced researchers in the field.
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