Question: Consider the network: model = models.Sequential () model.add(layers. Dense(64, activation = 'relu', input_shape =(10000),))#layer1 model.add(layers.Dense(64, activation = 'relu')) # layer 2 model.add(layers.Dense(46, activation = 'softmax'))

Consider the network: model = models.Sequential () model.add(layers. Dense(64, activation =

Consider the network: model = models.Sequential () model.add(layers. Dense(64, activation = 'relu', input_shape =(10000),))#layer1 model.add(layers.Dense(64, activation = 'relu')) \# layer 2 model.add(layers.Dense(46, activation = 'softmax')) \# layer 3 The classification problem is Select one: a. Multi-label, multi-class (46 classes) b. Single label, multi-class ( 64 classes) c. Single label, multi-class (46 classes) d. Single label, multi-class (unknown number of classes)

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