input: Write a python function to fit a linear regression model and predict values given x and y arrays.
  assert np.allclose(predict_values(np.array([[7,5,3,9,8,4]]).T, np.array([7,3,4,6])), [5.8, 4.6, 3.4, 6.8, 6.2, 5.0])
  assert np.allclose(predict_values(np.array([[1,2,3]]).T, np.array([1,2,3])), [1, 2, 3])
  assert np.allclose(predict_values(np.array([[10,20,30]]).T, np.array([100,200,300])), [100, 200, 300])
output: def predict_values(x, y):
      from sklearn.linear_model import LinearRegression
      import numpy as np
      
      model = LinearRegression()
      model.fit(x, y)
      
      predictions = model.predict(x)
      return predictions