Part#1 - Clustering 1) Step #1 - load Scikit_Learn and Numpy. 2) We're going to create a synthetic dataset using this code # synthetic classification dataset from numpy import where from sklearn.datasets import make_classification from matplotlib import pyplot # define dataset X, y = make_classification(n_samples=1000, n_features=2, n_informative=2, n_redundant=0, n_clusters per_class=1, random_state=4) # create scatter plot for samples from each class for class_value in range(2): # get row indexes for samples with this class row_ix = where(y == class_value) # create scatter of these samples pyplot.scatter(X[row_ix, 0], X[row_ix, 1]) # show the plot # CODE INTENTIONALLY OMITTED - YOU SHOULD WRITE THE CODE HERE COPY THE OUTPUT TO YOUR WORD DOCUMENT