AI engineering glossary · Linear algebra
What is frobenius norm?
Frobenius norm: The size of a matrix computed as the square root of the sum of the squares of all its entries, as if it were one long vector. It is the usual measure for weight-decay penalties and for the error of matrix approximations.
Frobenius norm: an example
For [[1,2],[3,4]], the norm is sqrt(1 + 4 + 9 + 16) = sqrt(30), about 5.48.
Related terms
More Linear algebra terms
- Full rank
- Gaussian elimination
- Gram matrix
- Gram-Schmidt process
- Hadamard product
- Homogeneous coordinates
- Hyperplane
- Identity matrix
Where you learn it
Frobenius norm is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.