Chapter 8: Building an Extract Transform Machine Learning Use Case
Similar to Chapter 7, Building an Example ML Microservice, the aim of this chapter will be to try to crystallize a lot of the tools and techniques we have learned about throughout this book and apply them to a realistic scenario. This will be based on another use case introduced in Chapter 1, Introduction to ML Engineering, where we imagined the need to cluster taxi-ride data on a scheduled basis. We will explore this scenario so that we can outline the key decisions we would make if building a solution in reality, as well as discussing how to implement it by leveraging what has been covered in other chapters.
This use case will allow us to explore what is perhaps the most used pattern in Machine Learning (ML) solutions across the world—that of the batch inference process. Due to the nature of retrieving, transforming, and then performing ML on data, I have termed this Extract Transform Machine Learning ...
