Created
November 18, 2018 08:40
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| model = Sequential() | |
| model.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=input_shape)) | |
| model.add(Conv2D(64, (3, 3), activation='relu')) | |
| model.add(MaxPooling2D(pool_size=(2, 2))) | |
| model.add(Dropout(0.25)) | |
| model.add(Flatten()) | |
| model.add(Dense(128, activation='relu')) | |
| model.add(Dropout(0.5)) | |
| model.add(Dense(num_classes, activation='softmax')) |
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