Eigenvalues And - Eigenvectors

Eigenvalues and eigenvectors are the "characteristic" components of linear transformations, representing the scalar factors and directions where a matrix only stretches or shrinks a vector without rotating it.

: Eigenvectors define the principal axes of data variance, allowing for dimensionality reduction in machine learning. Eigenvalues and Eigenvectors

: Google’s original algorithm uses the dominant eigenvector of a web-link matrix to rank page importance. Eigenvalues and Eigenvectors