1) For the following logistic regression with three labeled data points given as: x (1) = 3 . >(1 =0 4.00 3.75- 3.50 x (2 ) = [3]. >(2) = 1 3.25 3.00 2.75 2.50 2.25 2.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 Manually, calculate the values of all variables of the logistic regression algorithm below for the first iteration, n=1. Use a = 0.1, and initial conditions b = 0, W = [H. Show your work. Forward Propagation Z =WTx+b Logistic Regression (vectorized) with one perceptron A = o(Z) - X1 X = 1- key .. xin , shape (n, m) Backward Propagat - Xnx dZ = A - Y W = shape (nx, 1) dW = -XdZT LWnx. m Y = ly(1) db = np.sum(dZ) /m ... y(m)], shape (1, m) A = la(1) W:=W- adW ... a(m)], shape (1, m) Z = [z(1) ... z(m)], shape (1, m) b := b -adb L = [1(1) ... [(m)], shape (1, m) J = scalar