Chapter 11: Data Modeling – Regression Modeling
In this final chapter on data modeling, you will learn details about linear regression using the sklearn library's LinearRegression method, and non-linear regression modeling using the sklearn library's RandomForestRegressor method. As you learn more about these methods, you will also learn details about measuring model performance using measures such as the sum of square error and root mean squared error, as well as powerful visual methods, including constructing histograms of model errors and other plotting methods.
By the end of this chapter, you will have brought together all you have learned about data modeling and be ready to address a wide range of business and technical data challenges.
This chapter covers the following topics:
- An introduction to regression modeling
- Exploring regression modeling
- Model diagnostics
- Activity 11.01 – Implementing multiple regression
