text: #!/usr/bin/env python3
  # -*- coding: utf-8 -*-
  """
  Created on Thu Jul 19 12:57:46 2018
  
  @author: ryanwinfree
  """
  
  # Data Preprocessing
  
  # Importing the libraries
  import numpy as np
  import matplotlib.pyplot as plt
  import pandas as pd
  
  # Importing the dataset 
  dataset = pd.read_csv('Data.csv')
  X = dataset.iloc[:, :-1].values
  Y = dataset.iloc[:, -1].values
  
  # Splitting the dataset into the Training set and Test set
  from sklearn.cross_validation import train_test_split
  X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.2, random_state = 0)
  
  # Feature Scaling (like normalization)
  from sklearn.preprocessing import StandardScaler
  sc_X = StandardScaler()
  X_train = sc_X.fit_transform(X_train)
  X_test = sc_X.transform(X_test)
  