Introduction to Machine Learning

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Abstract

This chapter talks about what machine learning is, how machine learning systems are classified, and examples of real-world applications of machine learning. It discusses some of the tools commonly used by data scientists to build machine learning solutions. Most machine learning scientists use one of two programming languages: Python or R. There are several different types of machine learning systems today. The classification of a machine learning system is usually based on the manner in which the system is trained and the manner in which the system can make predictions. Machine learning systems are classified as follows: supervised learning; unsupervised learning; semi-supervised learning; reinforcement learning; batch learning; incremental learning; instance-based learning; and model-based learning. These labels are not mutually exclusive; it is quite common to come across a machine learning system that falls into multiple categories. The chapter examines these classification labels in more detail.

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