input: Write a python function to create a simple neural network model using TensorFlow's Keras API.
  assert isinstance(create_model().layers[0], tf.keras.layers.Embedding)
  assert isinstance(create_model().layers[1], tf.keras.layers.LSTM)
  assert isinstance(create_model().layers[2], tf.keras.layers.Dense)
  assert isinstance(create_model().layers[3], tf.keras.layers.Dense)
output: def create_model(vocab_size=10000, embedding_dim=64, input_length=100):
      model = tf.keras.Sequential([
          tf.keras.layers.Embedding(input_dim=vocab_size, output_dim=embedding_dim, input_length=input_length),
          tf.keras.layers.LSTM(64),
          tf.keras.layers.Dense(64, activation='relu'),
          tf.keras.layers.Dense(1, activation='sigmoid')
      ])
      return model