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There are some matrices which are just not meant for computation. They are known as ill conditioned matrices. "Condition number" is something that tells how "bad" . Luckily, this function is already present in numpy (numpy.linalg.cond). Bigger condition number means ill conditioned matrix.

Find out at-least 5 such matrices and show how they are giving garbage values. (You can, for example, take a matrix A, calculate it's inverse (numpy.linalg.inv), and multiply the inverse again with A, and check if the matrix is an identity matrix)