input: Write a python function to calculate the mean squared error between two lists of actual and predicted values.
  assert mean_squared_error([1, 2, 3], [1, 2, 3]) == 0
  assert mean_squared_error([1, 2, 3], [2, 3, 4]) == 1
  assert mean_squared_error([1, 2, 3], [3, 2, 1]) == 2
output: def mean_squared_error(actual, predicted):
      return sum((a - p) ** 2 for a, p in zip(actual, predicted)) / len(actual)