The Reactive Machine Learning book is live!

At long last, I’m thrilled to announce that Reactive Machine Learning Systems is now available in early access form. I’ve been working on this book since the original post on reactive machine learning, last year. It’s great to be able to finally share the first phase of this work with the world.

The book is much like the data engineering collection here on Medium. I’ve tried to catalogue all of the real world details of building a full machine learning system that you don’t hear about in other algorithm-focused books. That’s not to say that I shy away from the complex details of machine learning, but I try to get very specific about the code that you’ll need to write, the infrastructure that you’ll need to stand up, and all the ways that it might go wrong.

nom nom, the data dog

Of course, all of these things are couched in terms of animals who do machine learning.

If you’ve seen any of my talks, you know what to expect: thrilling African adventures, catastrophic rainforest fires, and much more. Along our journey through the wild world of machine learning, we’ll encounter a vast array of different real world machine learning problems and the animals who work on them. It’s a safari worth taking, I promise you.

The book is being published by Manning, which is the absolutely perfect publisher for this topic, in my opinion. They’ve been at the heart of the reactive movement, publishing books on reactive application development, design patterns, and web applications. Manning is also the publisher of some great books on real world machine learning, data science, and, of course, big data. I really feel like they understand what engineers like me are trying to achieve in building fundamentally better applications like reactive machine learning systems.

Of course, there’s one last missing piece to this puzzle: you. I write posts here on Medium, because I want to share my ideas with my fellow members of the tech community and receive feedback. This has been a crucial part of developing these ideas and refining them into a more useful form.

Now that the book is available in this draft form, you can help guide my exploration of reactive machine learning. The Manning Early Access Program will provide readers of the book with regular updates as each chapter is completed. Readers also get access to a forum to discuss the book with each other, the staff at Manning, and me. It’s my hope that if you share your experiences exploring reactive machine learning, that I will be able to write a better book.

So, if you’re interested in reactive machine learning, I hope that you’ll join in on this next phase of the adventure and check out the book.