Norm

Measures similarity and projection between vectors.

Vectors with zero inner product; implies independence.

Number of linearly independent rows or columns.

Sensitivity of a function to input perturbations.

Mathematical foundation for ML involving vector spaces, matrices, and linear transformations.

Set of vectors closed under addition and scalar multiplication.

Vector whose direction remains unchanged under linear transformation.

Decomposes a matrix into orthogonal components; used in embeddings and compression.