An Analytical Review of Machine Learning Methodologies - Nitin S. Shrirao; Sarita B. Patil; Dnyaneshwar S. Jadhav (Recent Trends in Mathematics, 2026)
Machine Learning (ML) is a dynamic and rapidly developing area of computer science that enables the system to learn from data and improve its performance without clear programs. Rooted in statistical theory and computer algorithms, ML has become a major technology that progresses in artificial intelligence. It strengthens the detection of the recommendations and speech for extensive applications from autonomous vehicles and medical diagnoses. This paper has reviewed the basics of machine learning, including its historical development, major algorithms and major applications. The evolution of machine learning, which includes deep learning and neural networks, begins with the basic theory of the theorem and the minimum square method, significantly contributed to by pioneers such as Allen Turing and Arthur Samuel. While the machine is shaping the learning industries and affecting daily life, it is important to understand its main principles and paths to navigate the future of intelligent systems.
Keywords: Machine Learning; artificial intelligence; reinforcement learning; supervised learning; unsupervised learning