input: Write a function to perform polynomial regression using scikit-learn.
  assert polynomial_regression(X_train, y_train, X_test, degree=2) == y_pred
  assert polynomial_regression(X_train, y_train, X_test, degree=3) == y_pred_degree_3
  assert polynomial_regression(X_train, y_train, X_test, degree=4) == y_pred_degree_4
output: def polynomial_regression(X_train, y_train, X_test, degree=2):
      from sklearn.preprocessing import PolynomialFeatures
      from sklearn.linear_model import LinearRegression
      from sklearn.pipeline import make_pipeline
      
      model = make_pipeline(PolynomialFeatures(degree), LinearRegression())
      model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      
      return y_pred