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import keras
import jovian
Using TensorFlow backend.
import numpy as np

from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten, Add, BatchNormalization
from keras.layers import Convolution2D, MaxPooling2D, SeparableConv2D
from keras.utils import np_utils

from keras.datasets import mnist

from pprint import pprint
(X_train, y_train), (X_test, y_test) = mnist.load_data()
print (X_train.shape)
from matplotlib import pyplot as plt
%matplotlib inline
plt.imshow(X_train[6], cmap='gray')
(60000, 28, 28)
<matplotlib.image.AxesImage at 0x7f9d0900beb8>
Notebook Image
X_train = X_train.reshape(X_train.shape[0], 28, 28,1)
X_test = X_test.reshape(X_test.shape[0], 28, 28,1)