from sklearn.cross_validation import train_test_split
x_train, x_test, y_train, y_test = train_test_split(x, y , train_size = 0.7, random_state =  90)

normalizing methods : https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/normalize-data
                        https://en.wikipedia.org/wiki/Feature_scaling
                        we apply the normalizing methods to the training data first, then seperately to the test data to compare!