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Nov 18th, 2018
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  1. model = Sequential()
  2. model.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=input_shape))
  3. model.add(Conv2D(64, (3, 3), activation='relu'))
  4. model.add(MaxPooling2D(pool_size=(2, 2)))
  5. model.add(Dropout(0.25))
  6. model.add(Flatten())
  7. model.add(Dense(128, activation='relu'))
  8. model.add(Dropout(0.5))
  9. model.add(Dense(num_classes, activation='softmax'))
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