input: from typing import List
  
  
  def create_neural_network_model(stock_prices: List[float]) -> float:
      """Create a neural network model that takes in a trajectory of stock prices 
      and predicts the stock price for the next day.
      >>> create_neural_network_model([10, 10.4, 10.5, 10.6, 10.7, 10.9, 11])
      11.24
      """
output:     import numpy as np
      from sklearn.neural_network import MLPRegressor
  
      X = np.array(stock_prices[:-1]).reshape(-1, 1)
      y = np.array(stock_prices[1:])
  
      model = MLPRegressor(hidden_layer_sizes=(10,), max_iter=1000, random_state=42)
      model.fit(X, y)
  
      next_day_price = model.predict(np.array([stock_prices[-1]]).reshape(-1, 1))
      return round(next_day_price[0], 2)