(1) Use Python to generate a 2D not linearly separable data set with 50 data points. The data set should have approximately half positive and half negative instances. Create a scatter plot to visualize the data set. (2) Modify the training algorithm you developed in a.(2) to have a training algorithm that works on a nonseparable data set. Use the synthetic data set in b. (1) to test your algorithm. Show the error function curve. Plot the decision boundary on the scatter plot of the data set.