Feature-Engineering

This notebook provides some skills to perform Feature-Engineering on data.

Skills that are covered in this notebook:

1. Different types of variables
2. Problems in variables
3. Machine learning model requirements
4. Engineering missing values (NA) in numerical variables
5. Engineering missing values (NA) in categorical variables
6. missing value imputation methods
7. when to use each NA imputation method
8. Top coding, bottom coding and zero coding
9. Engineering rare values in categorical variables
10. Engineer labels of categorical variables
11. Engineering mixed variables
12. Engineering Dates
13. Feature Scaling
14. Gaussian Transformation
15. Discretisation
16. Engineering features with Feature_Engine