Summary

In this chapter, we learned how to build an image classifier using convents, and also how to use a pre-trained model. We covered tricks on how to speed up the process of training by using these pre-convoluted features. Also, we understood different techniques that can be used to understand what goes on inside a CNN.

In the next chapter, we will learn how to handle sequential data using recurrent neural networks.