내용 |
model = keras.Sequential([
keras.layers.Conv2D(32, (3, 3),
activation='relu',
input_shape=(28, 28, 1)),
keras.layers.MaxPooling2D((2, 2)),
keras.layers.Flatten(),
keras.layers.Dense(128, activation=tf.nn.relu),
keras.layers.Dense(10, activation=tf.nn.softmax)
])
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
train_X = train_images.reshape((train_images.shape[0], 28, 28, 1))
test_X = test_images.reshape((test_images.shape[0], 28, 28, 1))
model.fit(train_X, train_labels, epochs=8)
test_loss, test_acc = model.evaluate(test_X, test_labels) |