input: def predict_housing_price(living_area: int, rooms: float) -> float:
      """Given the living area and number of rooms, predict the housing price using Linear Regression.
      >>> predict_housing_price(2200, 3)
      63300.0
      """
      data = [[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]]
      prices = [75000, 43000, 59000, 32000, 85000]
      
      import numpy as np
      from sklearn import linear_model
      
      X = np.array(data)
      y = np.array(prices)
      
      model = linear_model.LinearRegression()
      model.fit(X, y)
      
      return model.predict([[living_area, rooms]])[0]
output:     data = [[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]]
      prices = [75000, 43000, 59000, 32000, 85000]
      
      import numpy as np
      from sklearn import linear_model
      
      X = np.array(data)
      y = np.array(prices)
      
      model = linear_model.LinearRegression()
      model.fit(X, y)
      
      return model.predict([[living_area, rooms]])[0]