Regarding regularized NN equation in exercise 4

[hilmandayo]

I am referring to your exercise 4 code right now to complete mine. I think you've made a mistake on regularizing the NN backpropagation gradient (if I am wrong, pardon me). This is the equation:

And this is your code:

delta1 = d2.dot(a1) # 25x5000 * 5000x401 = 25x401
delta2 = d3.T.dot(a2) # 10x5000 *5000x26 = 10x26

theta1_ = np.c_[np.ones((theta1.shape[0],1)),theta1[:,1:]]
theta2_ = np.c_[np.ones((theta2.shape[0],1)),theta2[:,1:]]

theta1_grad = delta1/m + (theta1_*reg)/m
theta2_grad = delta2/m + (theta2_*reg)/m

Shouldn't it be

theta1_ = np.c_[np.zeros((theta1.shape[0],1)),theta1[:,1:]]
theta2_ = np.c_[np.zeros((theta2.shape[0],1)),theta2[:,1:]]

since we do not want to add anything to theta1_grad's and theta2_grad's first column (the bias)?

[panovr]

I also have this question.