Visualizing the training data

The following function will help you visualize the MNIST data. By passing in the index of a training example, the show_digit function will display that training image along with its corresponding label in the title:

# Visualize the data
import matplotlib.pyplot as plt
%matplotlib inline

#Displaying a training image by its index in the MNIST set
def display_digit(index):
    label = y_train[index].argmax(axis=0)
    image = X_train[index]
    plt.title('Training data, index: %d,  Label: %d' % (index, label))
    plt.imshow(image, cmap='gray_r')
    plt.show()
    
# Displaying the first (index 0) training image
display_digit(0)

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 /= 255
X_test /= 255
print("Train the matrix shape", X_train.shape)
print("Test the matrix shape", X_test.shape)

#One Hot encoding of labels.
from keras.utils.np_utils import to_categorical
print(y_train.shape)
y_train = to_categorical(y_train, 10)
y_test = to_categorical(y_test, 10)
print(y_train.shape)