Introduction

In the first two chapters, we were introduced to the concept of supervised machine learning in Python and the essential techniques required for loading, cleaning, exploring, and visualizing raw data sources. We discussed the criticality of the correlations between the specified inputs and desired output for the given problem, as well as how the initial data preparation process can sometimes take a lot of the time spent on the entire project.

In this chapter, we will delve into the model building process and will construct our first supervised machine learning solution using linear regression. So, let's get started.