In this chapter, we are going to introduce fundamental machine learning concepts, assuming that you have some basic knowledge of statistical learning and probability theory. You'll learn about the uses of machine learning techniques and the logical process that improves our knowledge about both nature and the properties of a dataset. The purpose of the entire process is to build descriptive and predictive models the can support business decisions.
Unsupervised learning aims to provide tools for data exploration, mining, and generation. In this book, you'll explore different scenarios with concrete examples and analyses, and you'll learn how to apply fundamental and more complex algorithms to solve specific problems.
In this introductory chapter, we are going to discuss:
- Why do we need machine learning?
- Descriptive, diagnostic, predictive, and prescriptive analyses
- Types of machine learning
- Why are we using Python?
