input: Write a python function to create and compile a simple neural network model using Keras.
  assert create_and_compile_model().summary() is not None
  assert isinstance(create_and_compile_model().layers[0], keras.layers.Dense)
  assert create_and_compile_model().loss == 'binary_crossentropy'
output: def create_and_compile_model():
      from keras.models import Sequential
      from keras.layers import Dense
      
      model = Sequential()
      model.add(Dense(10, input_dim=5, activation='relu'))
      model.add(Dense(1, activation='sigmoid'))
      model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
      
      return model