Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications Paperback – 31 May 2022

Very well written and enjoyable technical book.Whether you already work in this domain, want a refresher, or simply clarify some topics that are outside of your day-to-day duties, this book won't disappoint.

This book is absolutely brilliant and is a must read for anyone that worked in ML in academia and is moving to industry.I usually have to push myself to finish textbooks, but this is so nicely written that I kept reading with ease.This book is a masterpiece, and now my favourite ML book! It makes my top 5 ML recommendations along with: “Statistical rethinking”, “Machine learning a probabilistic perspective”, “Bayesian reasoning an machine learning” and “Dive into deep learning”My only negative is that the figures are printed in black and white, so I would have liked to have a pdf that came with the book to preview the figures in colour.

Very informative text on the design process

Received the book on time and in great condition.

I made my way through this book and ended up disappointed. Given the title, I had big hopes for it, but it did not deliver. The book is too shallow and feels disjointed at times, and it is not really about designing ML systems. Half of it was about general ML concepts, while the other half was about the parts of a system. Recommended only if you're getting started on with ML/MLOps; otherwise, steer clear of it.

I was waiting for this book to be delivered with very high expectations....when I received it, to say I was dissapointed with the print quality would be an understatement. For a book that cost me over £42, I expected much more in terms of quality and presentation. I have not read it yet, as I am considering returning it.

everyone can mention a few technologies like airflow and metaflow. copy a few very highlevel hello world code snippets ... where is the substance? where is an end to end example battle hardened for industry. the devil is in the detail. very disappointing!

this is an good book, but basically made by someone without any experience in delivering any production scale solution that are used to deliver actual sustained and increasing ROI on data investments.It takes at least a few decades of experience to deliver anything of value using data which does not invade people's privacy or try to change their behaviour or works on a business model that is not owing billions in fine to governments for destroying lives, markets, and free thinking.This book has promise and is not an outright fake, perhaps by the 6th or 7th edition of the book we will be able to see its contents mature to meaningful actionable items.But overall a good reading