Use ipython to solve it.

E4.8 We want to train a perceptron network with the following training set: 0 The initial weight matrix and bias are W(0) - 1 o, b(0) - 0.5 Plot the initial decision boundary, weight vector and input patterns. Which patterns are correctly classified using the initial weight and bias? i. ii. Train the network with the perceptron rule. Present each input vec- iii. Plot the final decision boundary, and demonstrate graphically iv. Will the perceptron rule (given enough iterations) always learn to tor once, in the order shown which patterns are correctly classified. correctly classify the patterns in this training set, no matter what initial weights we use? Explain. E4.8 We want to train a perceptron network with the following training set: 0 The initial weight matrix and bias are W(0) - 1 o, b(0) - 0.5 Plot the initial decision boundary, weight vector and input patterns. Which patterns are correctly classified using the initial weight and bias? i. ii. Train the network with the perceptron rule. Present each input vec- iii. Plot the final decision boundary, and demonstrate graphically iv. Will the perceptron rule (given enough iterations) always learn to tor once, in the order shown which patterns are correctly classified. correctly classify the patterns in this training set, no matter what initial weights we use? Explain