Principal Component, Machine Learning, Artificial Intelligence, Linear Algebra, Data Science.
kicker: When looking at our new covariance matrix (which you can think about as just covariance matrix from the “point of view” of the eigenvectors like in the composite image) — we notice that the maximum variance can be achieved when projecting along the x1 axis. The reason why we project onto