3. Linear Regression
Overview
This chapter covers regression problems and analysis, introducing us to linear regression, as well as multiple linear regression and gradient descent. By the end of this chapter, you will be able to distinguish between regression and classification problems. You will be able to implement gradient descent in linear regression problems, and also apply it to other model architectures. You will also be able to 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. In addition, you will be able to execute feature engineering to create dummy variables for constructing complicated linear models.