Create a 2-dimensional NumPy array A1 of shape (3,3) such that the first row should have the elements (1,2,4). The second row should have the elements (7,5,6). The third row should have the elements (9,4,11) Create a 2-dimensional NumPy array A2 of shape (3,3) such that the first row should have the elements (4,5,1). The second row should have the elements (8,1,2). The third row should have the elements (7,3,2) Create another NumPy array A3 which has a shape of 3x2 such that the first row should have the elements (3,1). The second row should have the elements (6,4). The third row should have the elements (2,5) (25 points) (Hint: use functions from numpy.linalig library) a. Find the diagonal (or off-diagonal) elements of A1 and A2 as a 1D array b. Compute the Matrix multiplication of A2 and A3 c. Compute the sum of the diagonal elements of A1 and A2 d. Compute the matrix determinant of A1, A2, A3 e. Compute the eigenvalues and eigenvectors of A1 and A2 f. Compute the inverse of a square matrix of A1 and A2 g. Compute the Moore-Penrose pseudoinverse of a matrices A1 and A2 h. Compute the QR decomposition of A1 and A2 i. Compute the singular value decomposition of A1 and A2