Machine learning (ML) is an amazing subfield of Artificial Intelligence (AI) that tries to mimic the learning behavior of humans. Similar to the way a baby learns by observing the examples it encounters, an ML algorithm learns the outcome or response to a future incident by observing the data points that are provided as input to it.

In this chapter, we will cover the following topics:

• ML versus software engineering
• Types of ML methods
• ML terminology—a quick review
• ML project pipeline
• Learning paradigm
• Datasets