000			01938 a2200181 4500
008			231221b |||||||| |||| 00| 0 eng d
020			_a9789355422675
082			_a005.74015 _bHUY
100			_aHuyen Chip
245			_aDesigning Machine Learning Systems: An Iterative Process for Production-Ready Applications
250			_a1st
260			_bShroff/O'Reilly _c2022 _aMumbai
300			_a388
520			_aMachine 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 Source: https://www.amazon.in/Designing-Machine-Learning-Systems-Production-Ready/dp/9355422679/ref=sr_1_1?crid=348O68VPJG5C6&keywords=9789355422675&qid=1703142428&sprefix=9789355422507%2Caps%2C374&sr=8-1
650			_aMachine Learning
906			_aBusiness Analytics
942			_c1 _2ddc
999			_c98180 _d98180