Application of Big Data and Machine Learning

Abstract

Today, Machine Learning (ML) is apart of our daily life. It has major advancements in its applications and research as well. ML is the study in which a machine is trained with past data and examples and uses algorithms to build the logic. Important ML applicationsare speech recognition, computer vision, bio-surveillance, robot or automation control, empirical science experiments, DNA classification, intrusion detection, astronomical data analysis, information security, transportation, etc. According to a recent survey, computer-generated insurance advice is helpful to customers. Using ML, determination of cover for a certain customer can be predicted. Choice of the mode of transportation can also be benefited from ML. ML predicts the mode of transportation for an individual to make their travel better. Travel modes may include private car, public transport (bus or train), or soft mode (walking or cycling). The very first step in applying ML is to define a problem. This step includes three important processes to be considered, namely, problem identification, the motivation behind problem solving, and the solution itself. This chapter presents the evolution of ML along with the purpose it serves. It also focuses on the ideas of concept learning along with the methods and algorithms therein.