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Last active December 5, 2017 17:40
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Reading data #deeplearning #InputOutput
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reading_data.md

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from keras.datasets import mnist
(X_train, y_train), (X_test, y_test) = mnist.load_data()
(X_train.shape, y_train.shape, X_test.shape, y_test.shape)
>> ((60000, 28, 28), (60000,), (10000, 28, 28), (10000,))

X_test = np.expand_dims(X_test,1)
X_train = np.expand_dims(X_train,1)
X_train.shape
>> (60000, 1, 28, 28)

y_train[:5]
>> array([5, 0, 4, 1, 9], dtype=uint8)
# hot encoding
y_train = onehot(y_train)
y_test = onehot(y_test)
y_train[:5]
array([[ 0.,  0.,  0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.],
       [ 1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.],
       [ 0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.]])
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