Linear algebra (cupynumeric.linalg)

Matrix and vector products

dot(a, b[, out])	Dot product of two arrays.
vdot(a, b[, out])	Return the dot product of two vectors.
inner(a, b[, out])	Inner product of two arrays.
outer(a, b[, out])	Compute the outer product of two vectors.
matmul(a, b, /[, out, casting, dtype])	Matrix product of two arrays.
tensordot(a, b[, axes, out])	Compute tensor dot product along specified axes.
einsum(expr, *operands[, out, dtype, ...])	Evaluates the Einstein summation convention on the operands.
einsum_path(expr, *operands[, optimize])	Evaluates the lowest cost contraction order for an einsum expression by considering the creation of intermediate arrays.
linalg.matrix_power(a, n)	Raise a square matrix to the (integer) power n.
linalg.multi_dot(arrays, *[, out])	Compute the dot product of two or more arrays in a single function call, while automatically selecting the fastest evaluation order.

Decompositions

linalg.cholesky(a)	Cholesky decomposition.
linalg.qr(a)	Compute the qr factorization of a matrix.
linalg.svd(a[, full_matrices])	Singular Value Decomposition.

Norms and other numbers

linalg.norm(x[, ord, axis, keepdims])	Matrix or vector norm.
trace(a[, offset, axis1, axis2, dtype, out])	Return the sum along diagonals of the array.

Solving equations and inverting matrices

linalg.solve(a, b[, out])

Solve a linear matrix equation, or system of linear scalar equations.