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# Linear algebra (`numpy.linalg`)

## Matrix and vector products

`dot` () |
`vdot` (a, b) | Return the dot product of two vectors.
`inner` (a, b) | Inner product of two arrays.
`outer` (a, b) | Returns the outer product of two vectors.
`tensordot` (a, b[, axes]) | Returns the tensor dot product for (ndim >= 1) arrays along an axes.
`linalg.matrix_power` (M, n) | Raise a square matrix to the (integer) power n.
`kron` (a, b) | Kronecker product of two arrays.

## Decompositions

`linalg.cholesky` (a) | Cholesky decomposition.
`linalg.qr` (a[, mode]) | Compute QR decomposition of a matrix.
`linalg.svd` (a[, full_matrices, compute_uv]) | Singular Value Decomposition.

## Matrix eigenvalues

`linalg.eig` (a) | Compute eigenvalues and right eigenvectors of an array.
`linalg.eigh` (a[, UPLO]) | Eigenvalues and eigenvectors of a Hermitian or real symmetric matrix.
`linalg.eigvals` (a) | Compute the eigenvalues of a general matrix.
`linalg.eigvalsh` (a[, UPLO]) | Compute the eigenvalues of a Hermitean or real symmetric matrix.

## Norms and other numbers

`linalg.norm` (x[, ord]) | Matrix or vector norm.
`linalg.cond` (x[, p]) | Compute the condition number of a matrix.
`linalg.det` (a) | Compute the determinant of an array.
`trace` (a[, offset, axis1, axis2, ...]) | Return the sum along diagonals of the array.

## Solving equations and inverting matrices

`linalg.solve` (a, b) | Solve the equation `a x = b` for `x`.
`linalg.tensorsolve` (a, b[, axes]) | Solve the tensor equation a x = b for x
`linalg.lstsq` (a, b[, rcond]) | Return the least-squares solution to an equation.
`linalg.inv` (a) | Compute the inverse of a matrix.
`linalg.pinv` (a[, rcond]) | Compute the (Moore-Penrose) pseudo-inverse of a matrix.
`linalg.tensorinv` (a[, ind]) | Find the ‘inverse’ of a N-d array

## Exceptions

`linalg.LinAlgError` | # Error object

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