input: 
  from typing import List
  
  import numpy as np
  import tensorflow as tf
  
  def predict_next_day_stock_price(trajectory: List[float]) -> float:
      """
      Given a trajectory of stock prices, this function creates a neural network model to predict the stock price for the next day.
  
      Example:
      >>> predict_next_day_stock_price([10, 10.4, 10.5, 10.6, 10.7, 10.9, 11])
      11.2
      """
      model = tf.keras.Sequential([
          tf.keras.layers.Dense(64, activation='relu', input_shape=(7, )),
          tf.keras.layers.Dense(1)
      ])
  
      model.compile(loss='mean_squared_error', 
                    optimizer='adam',
                    metrics=['accuracy'])
  
      input_data = np.array([trajectory])
      predictions = model.predict(input_data)
  
      return predictions[0][0]
  
output:     model.fit(input_data, np.array([trajectory[-1]]), epochs=100, verbose=0)