Normalization is a technique that rescales the values of the variables in a data set to a common range, such as
[0,1] or [-1,1]. Normalization can help reduce the effect of outliers, improve the performance of some algorithms, and make the interpretation of the regression coefficients easier and more consistent.
Normalization can be done using different methods, such as min-max scaling, z-score scaling, or unit vector scaling.
References:Guide to Business Data Analytics, page 41; Introduction to Business Data Analytics: A Practitioner View, page 12.