With the enormous increase of digital information from the different real-time applications, the amount of available information has rapidly grown.

In day-to-day life, individuals and business organizations often generate, exchange, or receive a huge amount of data; for instance, Google, Facebook, and Amazon deal with more than billions of digital information.

Automating the decision-making over large-scale data is a computationally-intensive task while adopting the traditional data mining models. Hence, machine learning models have been widely utilized to deal with classification, clustering, or regression problems in massive continuous or discrete data.

Machine learning automatically gains the knowledge from the previous data to provide the predictions for the new data through the gradual improvement in its learning behavior.

It greatly assists the decision-making for the structured, unstructured, and semi-structured data with the different types of machine learning algorithms.

Machine learning models have been widely applied to business, science, and engineering applications to enhance decision-making over large data with minimal computation cost.