Big Data Analytics with Machine Learning

Machine learning is an intersection of Artificial Intelligence and statistics and is the ability of a system to improve its understanding and decision‐making with experience. This chapter explains the relationship between the concept of big data analytics and machine learning, including various supervised and unsupervised machine learning techniques. Various social applications of big data, namely, health care, social analysis, finance, and security, are investigated with suitable use cases. There are two types of machine learning algorithms: supervised; and unsupervised. Support vector machines (SVM) are one of the supervised machine learning techniques. SVM can perform regression, outlier detection, and linear and nonlinear classification. A clustering technique is used when the specific target or the expected output is not known to the data analyst. It is popularly termed as unsupervised classification. In a clustering technique, the data within each group are remarkably similar in their characteristics.