Machine Learning Design Patterns

Chapter 1. The Need for Machine Learning Design Patterns

In engineering disciplines, design patterns capture best practices and solutions to commonly occurring problems. They codify the knowledge and experience of experts into advice that all practitioners can follow. This book is a catalog of machine learning design patterns that we have observed in the course of working with hundreds of machine learning teams.

What Are Design Patterns?

The idea of patterns, and a catalog of proven patterns, was introduced in the field of architecture by Christopher Alexander and five coauthors in a hugely influential book titled A Pattern Language (Oxford University Press, 1977). In their book, they catalog 253 patterns, introducing them this way:

Each pattern describes a problem which occurs over and over again in our environment, and then describes the core of the solution to that problem, in such a way that you can use this solution a million times over, without ever doing it the same way twice.

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Each solution is stated in such a way that it gives the essential field of relationships needed to solve the problem, but in a very general and abstract way—so that you can solve the problem for yourself, in your own way, by adapting it to your preferences, and the local conditions at the place where you are making it.

For example, a couple of the patterns that incorporate human details when building a home are Light on Two Sides of Every Room and Six-Foot Balcony. Think of your favorite room ...