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# Eigenvalues and eigenvectors

Put content here**Eigenvalues and eigenvectors** capture the intrinsic stretching/compressing directions of a linear transformation. For a square matrix $A$, a nonzero vector $v$ is an **eigenvector** with **eigenvalue** $\lambda$ if $Av = \lambda v$. Eigenvalues reveal fundamental properties: invertibility, stability, diagonalizability, and more.

# Parents

* Matrices
* Linear transformations
* Matrices⏎