NumPy offers a plethora of functions for executing linear algebra operations on arrays, including matrix multiplication, transposition, inversion, and decomposition. Key functions include:

• dot(): Computes the dot product of two arrays;
• transpose(): Transposes an array;
• inv(): Computes the inverse of a matrix;
• linalg.svd(): Performs the singular value decomposition of a matrix;
• linalg.eig(): Determines the eigenvalues and eigenvectors of a matrix.