Course 2 Week 1 Gradient_Checking assigmnet

I have written and thoroughly checked my code still getting following error in Exercise 4 - gradient_check_n

There is a mistake in the backward propagation! difference = 1.0

AssertionError Traceback (most recent call last)
6 expected_values = [0.2850931567761623, 1.1890913024229996e-07]
7 assert not(type(difference) == np.ndarray), “You are not using np.linalg.norm for numerator or denominator”
----> 8 assert np.any(np.isclose(difference, expected_values)), “Wrong value. It is not one of the expected values”

AssertionError: Wrong value. It is not one of the expected values

One thing to check is that you only add and subtract \epsilon from one element at a time, not from the entire vector at once in every iteration.

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