Deliver toUnited Arab Emirates
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

Description:

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references.


About the Author

Chip Huyen (https: //huyenchip.com) is a co-founder of Claypot AI, a platform for real-time machine learning. Through her work at NVIDIA, Netflix, and Snorkel AI, she has helped some of the world's largest organizations develop and deploy machine learning systems. She teaches CS 329S: Machine Learning Systems Design at Stanford, whose lecture notes this book is based on.

LinkedIn included her among Top Voices in Software Development (2019) and Top Voices in Data Science & AI (2020). She is also the author of four bestselling Vietnamese books, including the series Xach ba lo len va Di (Pack Your Bag and Go). She also runs a Discord server on MLOps with over 6,000 members (https: //discord.com/invite/Mw77HPrgjF).

Reviews:

5.0 out of 5 stars Go-to reference for AI pipelines insights.

M. · 18 August 2025

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.

5.0 out of 5 stars A must read for any ML practitioner moving from academia to industry

V.V. · 1 July 2022

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.

5.0 out of 5 stars Fine product and delivery great

G.S. · 23 September 2024

Very informative text on the design process

5.0 out of 5 stars Delivered perfectly

J. · 29 November 2022

Received the book on time and in great condition.

3.0 out of 5 stars Disappointing.

A.F. · 17 September 2024

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.

2.0 out of 5 stars TERRIBLE PRINT QUALITY

M.E.U. · 4 November 2023

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.

1.0 out of 5 stars too shallow

c. · 1 May 2023

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!

3.0 out of 5 stars overall okay

G. · 4 December 2022

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

10/10 fantastic book

E.G.M. · 24 February 2025

Covers so so many important points of putting ML in production. Highly recommend

Comes with black white colors

u. · 3 October 2024

Poor page quality and black-white colors.

Good book

K. · 16 April 2025

Interesting book! i enjoyed reading it

A must read for an ML enthusiast

R. · 29 September 2025

I got it delivered on time and the book is a nice read for anyone who wants to get into the field of Machine Learning system development.

Indispensable

C.C. · 2 July 2023

This book is everything you need to know if you're developing Machine Learning systems, not only models, but the hole system. It's something basic you need to read if you want to have a better understanding of your path either as a data scientist, ML Engineer, etc.

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

Product ID: K1098107969
Condition: New

4.6

AED34039

Price includes VAT & Import Duties
Type: Paperback
Availability: In Stock

Quantity:

|

Order today to get by 7-14 business days

This item qualifies for free delivery

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Imported From: United Kingdom

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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

Product ID: K1098107969
Condition: New

4.6

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications-0
Type: Paperback

AED34039

Price includes VAT & Import Duties
Availability: In Stock

Quantity:

|

Order today to get by 7-14 business days

This item qualifies for free delivery

Returns & Warranty policies

Imported From: United Kingdom

At BOLO, we work hard to ensure the products you receive are new, genuine, and sourced from reputable suppliers.

BOLO is not an authorized or official retailer for most brands, nor are we affiliated with manufacturers unless specifically stated on a product page. Instead, we source verified sellers, authorized distributors or directly from the manufacturer.

Each product undergoes thorough inspection and verification at our consolidation and fulfilment centers to ensure it meets our strict authenticity and quality standards before being shipped and delivered to you.

If you ever have concerns regarding the authenticity of a product purchased from us, please contact Bolo Support. We will review your inquiry promptly and, if necessary, provide documentation verifying authenticity or offer a suitable resolution.

Your trust is our top priority, and we are committed to maintaining transparency and integrity in every transaction.

All product information, images, descriptions, and reviews originate from the manufacturer or from trusted sellers overseas. BOLO is not affiliated with, endorsed by, or an authorized retailer for most brands listed on our website unless stated otherwise.

While we strive to display accurate information, variations in packaging, labeling, instructions, or formulation may occasionally occur due to regional differences or supplier updates. For detailed or manufacturer-specific information, please contact the brand directly or reach out to BOLO Support for assistance.

Unless otherwise stated, all prices displayed on the product page include applicable taxes and import duties.

BOLO operates in accordance with the laws and regulations of United Arab Emirates. Any items found to be restricted or prohibited for sale within the UAE will be cancelled prior to shipment. We take proactive measures to ensure that only products permitted for sale in United Arab Emirates are listed on our website.

All items are shipped by air, and any products classified as “Dangerous Goods (DG)” under IATA regulations will be removed from the order and cancelled.

All orders are processed manually, and we make every effort to process them promptly once confirmed. Products cancelled due to the above reasons will be permanently removed from listings across the website.

Description:

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references.


About the Author

Chip Huyen (https: //huyenchip.com) is a co-founder of Claypot AI, a platform for real-time machine learning. Through her work at NVIDIA, Netflix, and Snorkel AI, she has helped some of the world's largest organizations develop and deploy machine learning systems. She teaches CS 329S: Machine Learning Systems Design at Stanford, whose lecture notes this book is based on.

LinkedIn included her among Top Voices in Software Development (2019) and Top Voices in Data Science & AI (2020). She is also the author of four bestselling Vietnamese books, including the series Xach ba lo len va Di (Pack Your Bag and Go). She also runs a Discord server on MLOps with over 6,000 members (https: //discord.com/invite/Mw77HPrgjF).

Reviews:

5.0 out of 5 stars Go-to reference for AI pipelines insights.

M. · 18 August 2025

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.

5.0 out of 5 stars A must read for any ML practitioner moving from academia to industry

V.V. · 1 July 2022

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.

5.0 out of 5 stars Fine product and delivery great

G.S. · 23 September 2024

Very informative text on the design process

5.0 out of 5 stars Delivered perfectly

J. · 29 November 2022

Received the book on time and in great condition.

3.0 out of 5 stars Disappointing.

A.F. · 17 September 2024

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.

2.0 out of 5 stars TERRIBLE PRINT QUALITY

M.E.U. · 4 November 2023

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.

1.0 out of 5 stars too shallow

c. · 1 May 2023

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!

3.0 out of 5 stars overall okay

G. · 4 December 2022

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

10/10 fantastic book

E.G.M. · 24 February 2025

Covers so so many important points of putting ML in production. Highly recommend

Comes with black white colors

u. · 3 October 2024

Poor page quality and black-white colors.

Good book

K. · 16 April 2025

Interesting book! i enjoyed reading it

A must read for an ML enthusiast

R. · 29 September 2025

I got it delivered on time and the book is a nice read for anyone who wants to get into the field of Machine Learning system development.

Indispensable

C.C. · 2 July 2023

This book is everything you need to know if you're developing Machine Learning systems, not only models, but the hole system. It's something basic you need to read if you want to have a better understanding of your path either as a data scientist, ML Engineer, etc.

Similar suggestions by Bolo

More from this brand

Similar items from “Productivity”