Skopt Tutorial - Load & Transform Data

load_mnist.py

from keras.datasets import mnist
(X_train, y_train), (X_test, y_test) = mnist.load_data()

#Scale the data to between 0 and 1
X_train = X_train/ 255
X_test = X_test/ 255

#Flatten arrays from (28x28) to (784x1)
X_train = X_train.reshape(60000,784)
X_test = X_test.reshape(10000,784)

#Convert the y's to categorical to use with the softmax classifier
from keras.utils import np_utils
y_train = np_utils.to_categorical(y_train, 10)
y_test = np_utils.to_categorical(y_test, 10)

#Establish the input shape for our Networks.
input_shape= X_train[0].shape