I don't know that I fully understand your question, but let me give a shot at answering what I think you're asking.
The reactive manifesto led to a few books applying the principles of reactive systems design to various contexts, including this excellent book on Reactive Design Patterns. My book is absolutely influenced by material in that book, but the two books are really about different things. RDP is all about very general design patterns for systems design. Machine Learning Systems can be viewed as a collection of design patterns for machine learning systems specifically. You don't have to have read RDP to read my book. But certainly, I would expect some readers to find value in both.
If your question is more generally about design patterns and not that specific book, then I'm a bit fuzzier on what the question is. The main topic of my book is how to build machine learning systems. I specifically talk about all of the different components that will need to be implemented; that's what Part 2, the bulk of the book, is about. Those components aren't really skippable for you to have a working production grade machine learning system. Along the way, I present some ways that you could implement those components, using some reactive design patterns but a lot more things which could just be described as programming techniques or design principles. The tools in the book, Scala, Akka, and Spark, are really there to just make it possible to implement these ideas, but I'm not particularly concerned with selling any readers on the use of those specific tools. I'm trying to help build your understanding of how to build whole machine learning systems.
Thanks for the answer, I reckon my question was to vague.
Jeff Smith wrote: Along the way, I present some ways that you could implement those components, using some reactive design patterns but a lot more things which could just be described as programming techniques or design principles.