Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications

14. Advanced Machine Learning

14.1 Introduction

We’ve covered the basics of machine learning but only scratched the surface of what there is to know. In this chapter, we’ll give a small glimpse of what else is out there. Our goal is to provide enough information to get you started and to help you find the search terms to learn more on your own.

Neural networks make nice examples for a few reasons. They can reduce to familiar models, like linear regression, in special cases. They have many parameters that you can adjust to show what happens as a simple model becomes more complex. This lets you see how generalization performance behaves as you move from simpler models to more complex models. You can also see that simple models have trouble representing ...