input: Write a function to create a Python neural network model that takes in a given trajectory of stock prices and predicts the stock price for the next day. The model should be built using TensorFlow and Keras. The function should return the compiled model. Additionally, write the necessary code snippet to use the model to make a prediction using the provided input data.
  
  def create_model():
      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'])
  
      return model
      
  if __name__ == "__main__":
      model = create_model()
  
      input_data = np.array([[10, 10.4, 10.5, 10.6, 10.7, 10.9, 11]])
      predictions = model.predict(input_data)
  
      print(f"Predicted stock price for the next day is: {predictions[0][0]}")
output: 
  def create_model():
      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'])
  
      return model
  