
Description:
From the Back Cover
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.
This book will help you tackle scenarios such as:
- Engineering data and choosing the right metrics to solve a business problem
- Automating the process for continually developing, evaluating, deploying, and updating models
- Developing a monitoring system to quickly detect and address issues your models might encounter in production
- Architecting an ML platform that serves across use cases
- Developing responsible ML systems
About the Author
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).
Details:
Visit the O'Reilly Media Store
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
QAR36122
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Order today to get by 7-14 business days
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Visit the O'Reilly Media Store
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

QAR36122
Quantity:
Order today to get by 7-14 business days
This item qualifies for free delivery
Imported From: United Kingdom
At BOLO, we work hard to ensure the products you receive are new, genuine, and sourced from reputable suppliers.
Every product in the BOLO catalogue is sourced through our Verified Global Supply Network of 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.
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 Qatar. Any items found to be restricted or prohibited for sale within the Qatar will be cancelled prior to shipment. We take proactive measures to ensure that only products permitted for sale in Qatar 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:
From the Back Cover
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.
This book will help you tackle scenarios such as:
- Engineering data and choosing the right metrics to solve a business problem
- Automating the process for continually developing, evaluating, deploying, and updating models
- Developing a monitoring system to quickly detect and address issues your models might encounter in production
- Architecting an ML platform that serves across use cases
- Developing responsible ML systems
About the Author
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).
Details:
Similar suggestions by Bolo
More from this brand
Similar items from “Productivity”
Share with
Or share with link
https://www.bolo.qa/products/K1098107969