Exploring Machine Learning Methods: A Detailed Survey

Abstract

Machine learning is a computer science area that allows computers to learn without unequivocal programming. It is utilized in numerous computational tasks where it is quite difficult to design and program specific output algorithms. Thus, it is widely used in computer science, artificial intelligence, and other fields. Developing efficient applications for machine learning, however, requires understanding the smart systems and algorithms needed to build it. One of machine learning's core goals is to train computers to use the information to solve a specific issue. In this survey, we tend to present a decent line for ML and the different techniques used in it. The paper also outlines the mechanisms of ML algorithms. It has been found that the results of several machine learning techniques depend on the application areas on which they are applied. These challenges are meant to capture the entire process of a successful machine learning concept, including performance, infusion, and impact.