Week2 Practice Lab - Gradient calculation

Course Q&A Machine Learning Specialization Supervised ML: Regression and Classification
1

I am apparently not finding any problem with the calculation of the gradient, but I am getting the following error, please advise.

Gradient at initial w, b (zeros): -0.04747762052631062 -0.007323908939747608
Using X with shape (4, 1)

AssertionError Traceback (most recent call last)
in
6 print(‘Gradient at initial w, b (zeros):’, tmp_dj_dw, tmp_dj_db)
7
----> 8 compute_gradient_test(compute_gradient)

~/work/public_tests.py in compute_gradient_test(target)
60 dj_dw, dj_db = target(x, y, initial_w, initial_b)
61 #assert dj_dw.shape == initial_w.shape, f"Wrong shape for dj_dw. {dj_dw} != {initial_w.shape}"
—> 62 assert dj_db == -2, f"Case 1: dj_db is wrong: {dj_db} != -2"
63 assert np.allclose(dj_dw, -10.0), f"Case 1: dj_dw is wrong: {dj_dw} != -10.0"
64

AssertionError: Case 1: dj_db is wrong: -0.6640625 != -2

2

There appears to be an error with your calculation of the gradient of the bias (dj_db).

3

Could you please have a look and give some hints on the error that you mentioned here.

4

I have solved it. The assignment has been submitted.