Introduction to Feature Engineering in R

Creating Features from Categorical Data
-In this chapter, you will learn how to change categorical features into numerical representations that models can interpret. You'll learn about one-hot encoding and using binning for categorical features.

Creating Features from Numeric Data
-In this chapter, you will learn how to manipulate numerical features to create meaningful features that can give better insights into your model. You will also learn how to work with dates in the context of feature engineering.

Transforming Numerical Features
- In this chapter, you will learn about using transformation techniques, like Box-Cox and Yeo-Johnson, to address issues with non-normally distributed features. You'll also learn about methods to scale features, including mean centering and z-score standardization.

Advanced Methods
-In the final chapter, we will use feature crossing to create features from two or more variables. We will also discuss principal component analysis, and methods to explore and visualize those results.