input: from typing import NoReturn
  
  
  def linear_regression_model() -> NoReturn:
      """ Implement a simple linear regression model in Python using the Scikit-learn library. 
      The code should read data from a CSV file, fit a linear regression model, predict the 
      values using the trained model, and visualize the results using Matplotlib.
      """
      import pandas as pd
      import matplotlib.pyplot as plt
      from sklearn import linear_model
  
      # Read data from CSV
      data = pd.read_csv('data.csv')
  
      # Set X and Y
      X = data['X']
      Y = data['Y']
  
      # Create linear regression model
      model = linear_model.LinearRegression()
  
      # Train the model
      model.fit(X, Y)
  
      # Make predictions
      Y_pred = model.predict(X)
  
      # Visualize the results
      plt.scatter(X, Y)
      plt.plot(X, Y_pred, color='red')
      plt.show()
output:     X = X.values.reshape(-1, 1)
      Y = Y.values.reshape(-1, 1)