Keras Deep Learning Cookbook

How to do it...

We will be using the mnist dataset. First, let's plot the mnist images without standardization:

from keras.datasets import mnistfrom matplotlib import pyplot(X_train, y_train), (X_test, y_test) = mnist.load_data()# create a grid of 3x3 imagesfor i in range(0, 9):    ax = pyplot.subplot(330 + 1 + i)    pyplot.tight_layout()    ax.tick_params(axis='x', colors='white')    ax.tick_params(axis='y', colors='white') pyplot.imshow(X_train[i], cmap=pyplot.get_cmap('gray'))# show the plotpyplot.show()

The output plot will be similar to the following screenshot:

For feature standardization, we are planning to use ImageDataGenerator.