Thank you for purchasing MEAP for MLOps Engineering at Scale. To get the most value from this book, you’ll want to have existing skills in data analysis with Python and SQL as well as have some experience with machine learning. I expect that if you are reading this book, you are interested in developing your expertise as a machine learning engineer and you are planning to deploy your machine learning based solutions to production.
This book is composed of three parts. In Part 1, I chart out the landscape of what it takes to put a machine learning system in production, describe an engineering gap between experimental machine learning code and production machine learning systems, and explain how serverless machine learning can help bridge the gap. By the end of Part 1, I’ll have taught you how to use serverless features of a public cloud (Amazon Web Services) to get started with a real-world machine learning use case, prepare a working machine learning data set for the use case, and ensure that you are prepared to apply machine learning to the use case.