The previous chapters can best be described as trying to read an image. This is a subfield in machine learning called computer vision (CV). With convolutional neural networks (Chapter 7, Convolutional Neural Networks – MNIST Handwriting Recognition), we found that the convolutional layers learned how to filter an image.
There is a common misconception that any machine learning (ML) worth doing has to come from neural networks and deep learning. This is decidedly not the case. Instead, one should view deep learning as a technique to get to one's goals; deep learning is not the end-all. The purpose of this chapter is to expose readers to some of the insights into making ML algorithms work better in production. The code for this chapter is exceedingly simple. The topic is trivial and widely considered by many to be solved. However, the insights...
