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mnist-test / app.py

Create app.py

dc0264f about 2 years ago

378 Bytes

	import keras
	from keras import layers
	from keras import models

	model = models.Sequential()
	model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(28, 28, 1)))
	model.add(layers.MaxPooling2D((2, 2)))
	model.add(layers.Conv2D(64, (3, 3), activation='relu'))
	model.add(layers.MaxPooling2D((2, 2)))
	model.add(layers.Conv2D(64, (3, 3), activation='relu'))
	model.summary()