Implement the "cal_cost" to compute the cost.

def cal_cost(theta, X, y):

 htheta = ... term1 = ... /* matrix_multiplication(log(htheta), y) term2 = ... /* matrix_multiplication(log(1-htheta+eps), (1-y)) J = - 1 / m * (term1 + term2) return cost

Need help with calculation and the the following terms calculation

1. The cross entropy cost function (J()) in logistic regression is shown below. It involves two terms, including ylog(h) and (1y)log(1h) where h is the function of x. J()=m1i=1m[y(i)log(h(x(i)))(1y(i))log(1h(x(i)))]