February 2018
Intermediate to advanced
378 pages
10h 14m
English
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))) ...Read now
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