Is it hard to generate an Identity matrix in Numpy by using the inverse of multiple matrices of A?

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No, it is not hard to generate an identity matrix in Numpy using the inverse of multiple matrices of A. In fact, it is a common method to check if a matrix A is invertible or not. If the product of the inverse of multiple matrices of A gives an identity matrix, then A is invertible. Here's an example code snippet:

import numpy as np

# creating a Numpy array A
A = np.array([[2, 3], [4, 5]])

# finding the inverse of A
inv_A = np.linalg.inv(A)

# multiplying inverse of A with A to get identity matrix
identity = np.matmul(A, inv_A)

print(identity)

Output:

[[1. 0.]
 [0. 1.]]

As we can see, we have generated an identity matrix using the inverse of matrix A.