Creating the network

Keras allows building the deep neural networks by adding new layers one by one. Note, that all layers should be familiar to you to this moment.

from keras.models import Sequential 
from keras.layers import Activation, Dropout, Flatten, Dense, BatchNormalization, Conv2D, MaxPool2D 
model = Sequential() 
 
model.add(Conv2D(16, (3, 3), padding='same', activation='relu', input_shape=(height, width, depth))) 
model.add(Conv2D(16, (3, 3), padding='same')) 
model.add(BatchNormalization()) 
model.add(Activation('relu')) 
model.add(MaxPool2D((2,2))) 
 
model.add(Conv2D(32, (3, 3), padding='same', activation='relu')) 
model.add(Conv2D(32, (3, 3), padding='same')) 
model.add(BatchNormalization()) 
model.add(Activation('relu')) 
model.add(MaxPool2D((2,2))) 
 
model.add(Conv2D(64, (3, 3), padding...