Chapter 1, Preparing and Understanding Data, covers the loading of data and demonstrates how to obtain an understanding of its structure and dimensions, as well as how to install the necessary packages.
Chapter 2, Linear Regression, provides you with a solid foundation before learning advanced methods such as Support Vector Machines and Gradient Boosting. No more solid foundation exists than the least squares linear regression.
Chapter 3, Logistic Regression, presents a discussion on how logistic regression and discriminant analysis is used in order to predict a categorical outcome. Multivariate adaptive regression splines have been added. This technique performs well, handles non-linearity, and is easy to explain. ...
