An Investigation into the Techniques and Uses of Machine Learning

Abstract

A branch of AI, machine learning emerged in the 1950s and has since grown into its own scientific discipline. Machine learning’s
origins may be traced to the 1950s, when the field saw little in the way of substantial study or advancements. Nevertheless, studies
in this area were revived, advanced, and continue to this day in the 1990s. This field of study has a lot of room for growth
in the years to come. The difficulty in analyzing and interpreting the ever-increasing data is the driving force behind this change.
Increasing amounts of data allow machine learning to operate on the premise of selecting the most appropriate model from
among existing data in order to apply to new data. Consequently, studies in machine learning will continue in tandem with the
growth of data. Machine learning’s background, its methodologies, its application domains, and previous studies are all part of
this body of work. Learning about machine learning and its applications has recently grown in popularity, and this project aims
to teach academics about it.