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Training a State-of-the-Art Model

This chapter introduces more advanced techniques for training an image classification model and getting state-of-the-art results. You can skip it if you want to learn more about other applications of deep learning and come back to it later—knowledge of this material will not be assumed in later chapters.

This is going to be much harder to do well than with our previous datasets because we’re using full-size, full-color images, which are photos of objects of different sizes, in different orientations, in different lighting, and so forth. So, in this chapter we’re going to introduce some important techniques for getting the most out of your dataset, especially when you’re training from scratch, or using transfer learning to train a model on a very different kind of dataset than the pretrained model used.