Programming, Numerical Analysis, Linear Algebra, Python.
to be square and of full-rank, i.e., all rows (or, equivalently, columns) must be linearly independent. Now let’s try to solve the above equations using the matrix inversion approach. A_inv = np.linalg.inv(A) x = np.dot(A_inv, y) print(x) The result will be : [ 2.20833333 -2.58333333 -0.18333333]