Keras Deep Learning Cookbook

Common code for samples

The following code list is used by all the samples in optimization. We import the relevant classes:

from __future__ import print_functionimport kerasfrom keras.datasets import mnistfrom keras.models import Sequentialfrom keras.layers import Dense, Dropoutbatch_size = 128num_classes = 10epochs = 20

(x_train, y_train), (x_test, y_test) = mnist.load_data()x_train = x_train.reshape(60000, 784)x_test = x_test.reshape(10000, 784)x_train = x_train.astype('float32')x_test = x_test.astype('float32')x_train /= 255x_test /= 255print(x_train.shape[0], 'train samples')print(x_test.shape[0], 'test samples')# convert class vectors to binary class matricesy_train = keras.utils.to_categorical(y_train, num_classes)y_test = keras.utils.to_categorical(y_test, ...