Maths for ML / Notation

\mathbf{A}\mathbf{v} = \lambda\mathbf{v}

eigenvalue / eigenvector

Linear algebraIntermediate

Say it “A v equals lambda v”

An eigenvector is a direction A only stretches (doesn't rotate); λ is how much it stretches.

Example

\begin{bmatrix}2&0\\0&1\end{bmatrix}\begin{bmatrix}1\\0\end{bmatrix} = 2\begin{bmatrix}1\\0\end{bmatrix}

In code

np.linalg.eig(A)

torch.linalg.eig(A)

Where you’ll see it in ML

PCA, spectral methods, stability of training dynamics.

Don’t confuse it with

$\lambda$ lambda Conventionally a regularization strength — or an eigenvalue in linear algebra.

Lessons that use it

← All 94 symbols