Introduction
PCA can give you as many principal components as there are features. The practical question is: how many should you keep? Keep too few and you lose important information; keep too many and you don't gain much.
This topic covers how to choose, how PCA works as a compression method (and how to "decompress"), and how to run PCA on datasets too large for memory.