Description: Principal component analysis (PCA) is a mainstay of modern data analysis- a black box that
is widely used but poorly understood. The goal of this paper is to dispel the magic behind this
black box. This tutorial focuses on building a solid intuition for how and why principal component
analysis works furthermore, it crystallizes this knowledge by deriving from simple intuitions, the
mathematics behind PCA . This tutorial does not shy away from explaining the ideas informally,
nor does it shy away from the mathematics. The hope is that by addressing both aspects, readers
of all levels will be able to gain a better understanding of PCA as well as the when, the how and
the why of applying this technique.
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