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 function should return the model.
  assert create_model() is not None
  import numpy as np
  model = create_model()
  input_data = np.array([[10, 10.4, 10.5, 10.6, 10.7, 10.9, 11]])
  predictions = model.predict(input_data)
  assert predictions is not None
  assert type(predictions[0][0]) == np.float32
output: def create_model():
      import tensorflow as tf
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense
  
      model = Sequential()
      model.add(Dense(10, input_shape=(7,), activation='relu'))
      model.add(Dense(1, activation='linear'))
      model.compile(optimizer='adam', loss='mean_squared_error')
      return model