Dataset.py

from keras.datasets import mnist

(x_train, y_train), (x_test, y_test) = mnist.load_data()

print(‘Training Data: {}’.format(x_train.shape))
print(‘Training Labels: {}’.format(y_train.shape))

Training Data: (60000L, 28L, 28L)
Training Labels: (60000L,)

print(‘Testing Data: {}’.format(x_test.shape))
print(‘Testing Labels: {}’.format(y_test.shape))

Testing Data: (10000L, 28L, 28L)
Testing Labels: (10000L,)

# EDA

fig, axs = plt.subplots(3, 3, figsize = (12, 12))
plt.gray()

for i, ax in enumerate(axs.flat):
ax.matshow(x_train[i])
ax.axis(‘off’)
ax.set_title(‘Number {}’.format(y_train[i]))

fig.show()