input: Write a python function to build and train a neural network model using Keras.
  assert model.evaluate(x_test, y_test)[1] < 2.0
  assert len(model.layers) == 2
  assert model.input_shape == (None, 6)
output: def build_and_train_model(x_train, y_train, x_test, y_test):
      from keras.models import Sequential
      from keras.layers import Dense
      
      model = Sequential()
      model.add(Dense(10, activation='relu', input_shape=(6,)))
      model.add(Dense(1))
      
      model.compile(optimizer='adam', loss='mean_squared_error', metrics=['accuracy'])
      model.fit(x_train, y_train, epochs=10, batch_size=32, verbose=0)
      
      return model