Exercise 3 about ml-coursera-python-assignments HOT 2 OPEN

# You need to return the following variables correctly 
ll_theta = np.zeros((num_labels, n + 1))

# Add ones to the X data matrix
X = np.concatenate([np.ones((m, 1)), X], axis=1)

# ====================== YOUR CODE HERE ======================
for c in np.arange(num_labels):
    initial_theta=np.zeros(n+1)
    options={'maxiter':50}
    res=optimize.minimize(lrCostFunction,initial_theta,(X,(y==c),lambda_),jac=True,method='TNC',options=options)
    all_theta[c]=res.x
# ============================================================
return all_theta`