Once You've Added All the Layers to a Keras Neural

Multiple Choice

Once you've added all the layers to a Keras neural network, you complete the Keras model by calling its compile method, as in: cnn.compile(optimizer='adam',
Loss='categorical_crossentropy',
Metrics=['accuracy'])
Which of the following statements about the arguments is false?

A) optimizer='adam' specifies the optimizer this model will use to adjust the weights throughout the neural network as it learns.
B) There are many optimizers -xe "optimizer:'adam'"xe "adam optimizer[adam optimizer]"'adam' performs well across a wide variety of models.
C) loss='xe "categorical_crossentropy loss function"xe "loss function:categorical_crossentropy"categorical_crossentropy' specifies the xe "loss function"loss function used by the optimizer in multi-classification networks like our convnet, which predicts 10 classes. As the neural network learns, the optimizer attempts to maximize the values returned by the loss function. The greater the loss, the better the neural network is at predicting what each image is.
D) metrics=['accuracy']-This is a list of the metrics that the network will produce to help you evaluate the model. We use the xe "accuracy of a model"accuracy metric to check the percentage of correct predictions.