Chapter 3. Regression Analysis

Note

Learning Objectives

By the end of this chapter, you will be able to:

• Describe regression models and explain the difference between regression and classification problems

• Explain the concept of gradient descent, how it is used in linear regression problems, and how it can be applied to other model architectures

• Use linear regression to construct a linear model for data in an x-y plane

• Evaluate the performance of linear models and use the evaluation to choose the best model

• Use feature engineering to create dummy variables for constructing more complicated linear models

• Construct time series regression models using autoregression

Note

This chapter covers regression problems and analysis, introducing us to linear regression as well as multiple linear regression, gradient descent, and autoregression.