input: Write a python function to plot a linear regression model using given x and y data.
  assert plot_linear_regression([1, 2, 3, 4, 5], [1, 4, 9, 16, 25]) == None
  assert plot_linear_regression([1, 2, 3], [1, 2, 3]) == None
  assert plot_linear_regression([1, 2, 3, 4], [2, 4, 6, 8]) == None
output: def plot_linear_regression(x, y):
      import matplotlib.pyplot as plt
      from sklearn.linear_model import LinearRegression
      import numpy as np
  
      x = np.array(x).reshape(-1, 1)
      y = np.array(y)
  
      model = LinearRegression()
      model.fit(x, y)
      y_pred = model.predict(x)
  
      plt.scatter(x, y, color='blue')
      plt.plot(x, y_pred, color='red')
      plt.xlabel('x')
      plt.ylabel('y')
      plt.title('Linear Regression')
      plt.show()