Learning the modeling basics
So far, we've talked about data modeling in a somewhat abstract sense. In this and the next chapter, we will focus on the tools that help us gain insights from data and construct some basic predictive models using that data. We will begin by defining the modeling landscape in more depth, then look at some of the tools provided directly in pandas.
Modeling tools
In Chapter 9, Data Modeling – Preprocessing, we introduced the scikit-learn (sklearn) LinearRegression method and showed how to fit a simple multiple linear regression model. While there is a vast range of modeling tools available for Python, sklearn is perhaps one of the most used for everything from regression to classification and even basic neural networks. The sklearn ecosystem is described (see https://scikit-learn.org/stable/) as follows:
- Simple and efficient tools for predictive data analysis
- Accessible to everybody, and reusable in various contexts
- Built...
