Farzad Mahmoodinobar

Dimensionality reduction through Principal Component Analysis (PCA). Farzad Mahmoodinobar · Follow Published in Towards Data Science · 12 min read · 10 hours ago — Photo by carlos lugo on Unsplash Principal Component Analysis or PCA is one of the most popular dimensionality reduction methodologies available to statisticians and machine learning practitioners. Before diving deeper into what this means, let’s talk about a few scenarios where we use such methodologies in our daily life, probably