Basic properties of generalized inverse are proved. A computational procedure is given. It is shown that a generalized inverse is reflexive if and only if it has the same rank as the matrix. Least squares and minimum norm inverses are defined and their characterization in terms of linear equations is provided. Moore–Penrose inverse is introduced and its existence and uniqueness is established.