input: from typing import List
  
  def train_neural_network(features: List[float]) -> float:
      """ Train a neural network to predict the price of a house given a set of features.
      >>> train_neural_network([0.8, 0.4, 0.7])
      """
      
      import numpy as np
      from keras.models import Sequential
      from keras.layers import Dense
  
      features = np.array([features])
  
      model = Sequential()
      model.add(Dense(64, input_dim=3, activation='relu'))
      model.add(Dense(32, activation='relu'))
      model.add(Dense(1, activation='linear'))
  
      model.compile(loss='mse', optimizer='adam', metrics=['mse'])
  
      model.fit(features, batch_size=3, epochs=200)
output:     predicted_price = model.predict(features)
      return predicted_price[0][0]