mnist_viz_tf.ipynb

Kernel: Unknown Kernel

try:
    from tensorflow import keras
except ModuleNotFoundError:
    %pip install -qq tensorflow
    from tensorflow import keras
import tensorflow as tf
import numpy as np
import scipy
import matplotlib.pyplot as plt
try:
    import pandas as pd
except ModuleNotFoundError:
    %pip install -qq pandas
    import pandas as pd
try:
    import sklearn
except ModuleNotFoundError:
    %pip install -qq scikit-learn
    import sklearn

from time import time
import os
figdir = "figures"


def savefig(fname): plt.savefig(os.path.join(figdir, fname))


# print(tf.__version__)
np.random.seed(0)

mnist = keras.datasets.mnist
(train_images, train_labels), (test_images, test_labels) = mnist.load_data()
train_images = train_images / 255.0
test_images = test_images / 255.0

# print(np.shape(train_images))
# print(np.shape(test_images))
#(60000, 28, 28)
#(10000, 28, 28)

plt.figure(figsize=(10, 10))
for i in range(25):
    plt.subplot(5, 5, i+1)
    plt.xticks([])
    plt.yticks([])
    plt.grid(False)
    plt.imshow(train_images[i], cmap=plt.cm.binary)
savefig("mnist-data.pdf")
plt.show()