input: 
  import numpy as np
  import tensorflow as tf
  
  def predict_next_day_price(input_data: list) -> float:
      """Create a neural network model that takes in a given trajectory of stock prices and predicts the stock price for the next day.
      For example:
      >>> predict_next_day_price([10, 10.4, 10.5, 10.6, 10.7, 10.9, 11])
      11.1
      """
      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'])
  
      predictions = model.predict(np.array([input_data]))
      return predictions[0][0]
  
output:     model.fit(np.array([input_data]), np.array([input_data[-1]]), epochs=100, verbose=0)