In the previous chapter, we trained a simple convolution neural network (CNN) model on the CIFAR-10 dataset. Here, we are going to demonstrate the case of using a pre-trained model as a feature extractor while removing the fully connected layer of the pre-trained model, and then we'll feed these extracted features or transferred values to a softmax layer.

The pre-trained model in this implementation will be the inception model, which will be pre-trained on ImageNet. But bear in mind that this implementation builds on the previous two chapters that introduced CNN.