This book will show you how to develop complex software (sometimes rooted in randomness) in small, controlled steps . It will also instruct you in how to begin developing solutions to machine learning problems using test-driven development (from here, this will be written as TDD). Mastering TDD is not something this book will achieve. Instead, this book will help you begin your journey and expose you to guiding principles, which you can use to creatively solve challenges as you encounter them.
We will answer the following three questions in this chapter:
After gaining answers to these questions, we will be ready to move on to tackling real problems. This book is about applying these concepts to solve machine learning problems. This chapter contains the largest theoretical explanation that we will see in the book, with the remainder of the theory being described by example.
Due to the focus on application, you will learn much more than simply the theory of TDD and BDD. However, there are aspects of practices that this book will not touch on. To read more about the theory and ideas, search the Internet for articles written by the following:
Kent Beck—The father of TDD
Dan North—The father of BDD
Martin Fowler—The father of refactoring. He has also created a large knowledge base on these topics
James Shore—One of the authors of The Art of Agile Development, who has a deep theoretical understanding of TDD, and explains the practical value of it quite well
These concepts are incredibly simple and yet can take a lifetime to master. When applied to machine learning, we must find new ways to control and/or measure the random processes inherent in the algorithm. This will come up in this chapter as well as others. In the next section, we will develop a foundation for TDD and begin to explore its application.