Hello,

I get this assertion error when I run the learning model. All the previous test cases have passed so I am unsure why the expected cost is different. Did anybody else run into this?

Thanks for your help!

```
AssertionError Traceback (most recent call last)
<ipython-input-111-9408a3dffbf6> in <module>
1 from public_tests import *
2
----> 3 model_test(model)
~/work/release/W2A2/public_tests.py in model_test(target)
127 assert type(d['costs']) == list, f"Wrong type for d['costs']. {type(d['costs'])} != list"
128 assert len(d['costs']) == 1, f"Wrong length for d['costs']. {len(d['costs'])} != 1"
--> 129 assert np.allclose(d['costs'], expected_output['costs']), f"Wrong values for d['costs']. {d['costs']} != {expected_output['costs']}"
130
131 assert type(d['w']) == np.ndarray, f"Wrong type for d['w']. {type(d['w'])} != np.ndarray"
AssertionError: Wrong values for d['costs']. [array(0.15900538)] != [array(0.69314718)]
```