input: Write a function to create a spam classifier model using Keras.
  assert create_spam_classifier().count_params() > 0
  assert isinstance(create_spam_classifier(), keras.Sequential)
output: def create_spam_classifier():
      from keras.models import Sequential
      from keras.layers import Dense, Dropout
  
      model = Sequential()
      model.add(Dense(64, input_dim=100, activation='relu'))
      model.add(Dropout(0.5))
      model.add(Dense(1, activation='sigmoid'))
  
      model.compile(loss='binary_crossentropy',
                    optimizer='adam',
                    metrics=['accuracy'])
      return model