Digital Transformation

CHAPTER 8Machine Learning

This chapter provides an understanding of machine learning technology, the mechanics and challenges, and the rationale for enterprises to move towards it. It also discusses the key steps that should be taken to build a machine learning model, the implementation methodology, and some of the typical industry solutions and use cases for deploying machine learning to predict future outcomes and make the enterprise intelligent.

Machine Learning Overview

Machine learning is the pattern recognition technology that allows machines and computer programs to automatically improve their performance through experience by learning, analyzing, and making predictions based on historical data. It performs data analysis by using algorithms that iteratively learn from that data and present insights. It provides consistent, repeatable decisions and results by learning from prior computations. Machine learning empowers the computer system to imitate the working of the human brain.

Understanding Machine Learning

Some of the characteristics of machine learning are described below:

• Machine learning is a subset of artificial intelligence, while deep learning is a subset of machine learning.
• Data science is a combination of machine learning, computer science, and visualization.
• Big data and data mining support machine learning, which, in turn, supports natural language processing, speech recognition patterns, computer vision, and simulated modeling.
• In a traditional ...