Exercise $6$

Please complete the compute$\_$gradient$\_$reg function below to modify the code below to calculate the following term

$\frac{}{m}{w}_j,$ for $j=0$dots$(n-1)$

The starter code will add this term to the $\frac{\text{d}\text{e}\text{l}\text{J}(w,b)}{\text{d}\text{e}\text{l}\text{w}}$ returned from compute$\_$gradient above to get the gradient for the regularized cost function.

If you get stuck, you can check out the hints presented after the cell below to help you with the implementation.

# UNQ$\_$C$6$

def compute$\_$gradient$\_$reg$($X$,$ y$,$ w$,$ b$,$ lambda$\_=1)$:

$"\text{'}"."$

Computes the gradient for logistic regression with regularization

Args:

X : $($ndarray Shape $($m$,$n$))$ data, m examples by $n$ features

y : $($ndarray Shape $($m$,))$ target value

w : $($ndarray Shape $(n),$