Summary

We covered a lot of ground in this first chapter. We introduced computer vision, the challenges associated with it, and some historical methods, such as SIFT and SVMs. We got familiar with neural networks and saw how they are built, trained, and applied. After implementing our own classifier network from scratch, we can now better understand and appreciate how machine learning frameworks work.

With this knowledge, we are now more than ready to start with TensorFlow in the next chapter.