input: def construct_regression_neural_network() -> Sequential:
      """Construct a neural network in Python that can perform basic regression.
      The network should be able to load data from a CSV file, split it into features
      and labels, and then perform training and evaluation using the given data.
      Example:
      >>> model = construct_regression_neural_network()
      >>> score = model.evaluate(X_test, y_test, verbose=0)
      >>> print('Test score:', score)
      Test score: 0.05
      """
output:     from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense
  
      model = Sequential()
      model.add(Dense(64, input_dim=1, activation='relu'))
      model.add(Dense(32, activation='relu'))
      model.add(Dense(16, activation='relu'))
      model.add(Dense(1, activation='linear'))
  
      model.compile(optimizer='adam', loss='mean_squared_error')
  
      return model