ABSTRACT
Usually, the term “machine learning” is interchangeable with artificial intelligence, however machine learning is in fact an artificial intelligence sub-area. It is also defined as predictive analysis or predictive modeling. This chapter covers a deep understanding of what machine learning is, how it is related to the internet of things (IoT) and what steps need to be taken while developing a machine-learning-based application. In data collection, data required for analysis is gathered from various sources such as web pages, emails, IoT sensors, text files etc. This data serves as the input to machine learning algorithms, to generate insights from it. The chapter uses different approaches like supervised, semi-supervised and unsupervised, or any other approach for developing a model. Machine learning is a category of algorithms that allows software applications to be trained and to learned without being explicitly programmed.
