Data Science, Factor Analysis, Data, Machine Learning, Statistics.
especially important to normalize features when they have different scales. For instance, when one feature is in miles and the other in minutes. Normalization also guarantees that principal components are: Linearly independent. Each principal component is a linear combination that is not made of