model = Sequential()
model.add(Conv2D(32, kernel_size=3, activation='relu', input_shape=(28,28,1)))
model.add(MaxPooling2D(pool_size=(3, 3)))
model.add(Conv2D(24, kernel_size=3, activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Flatten())
model.add(Dense(10, activation='softmax'))

model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])