Introduction to Principal Component Analysis

The sheer size of data in the modern age is not only a challenge for computer hardware but also the main bottleneck for the performance of many machine learning algorithms. The main goal of a PCA analysis is to identify patterns in data. PCA aims to detect the correlation between variables. If a strong correlation between variables exists, the attempt to reduce the dimensionality only makes sense. It is a statistical method used to reduce the number of variables in a data-set.