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
