PCA Principal Component Analysis: Theory and Practice

Principal Component Analysis (PCA) is one of the most widely used techniques in data science and machine learning. It is a dimensionality reduction method that transforms a large set of variables into a smaller one, preserving as much information as possible. In this article, we delve into the basic principles, applications, and advantages of PCA,…

Read More