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Defining model in keras (include_top = True)
Having include_top=True means that a fully-connected layer will be added at the end of the model. This is usually what you want if you want the model to actually perform classification. With include_top=True you can specify the parameter classes (defaults to 1000 for ImageNet). Web# Include_top is set to False, in order to exclude the model's fully-connected layers. conv_base = VGG16(include_top=False, weights='imagenet', input_shape=input_shape) # Defines how many layers to freeze during training. # Layers in the convolutional base are switched from trainable to non-trainable # depending on the size of the fine-tuning ... great white vs hammerhead size
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