Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications (Record no. 98180)

MARC details
000 -LEADER
fixed length control field 01938 a2200181 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 231221b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789355422675
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.74015
Cutter HUY
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Huyen Chip
245 ## - TITLE STATEMENT
Title Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
250 ## - EDITION STATEMENT
Edition statement 1st
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Shroff/O'Reilly
Date of publication, distribution, etc 2022
Place of publication, distribution, etc Mumbai
300 ## - PHYSICAL DESCRIPTION
Extent 388
520 ## - Remark
Summary, etc 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.<br/><br/>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.<br/><br/>This book will help you tackle scenarios such as:<br/><br/>Engineering data and choosing the right metrics to solve a business problem<br/>Automating the process for continually developing, evaluating, deploying, and updating models<br/>Developing a monitoring system to quickly detect and address issues your models might encounter in production<br/>Architecting an ML platform that serves across use cases<br/>Developing responsible ML systems<br/><br/>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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a Business Analytics
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Item type Book
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Collection Type Full call number Barcode Date last seen Cost, replacement price Koha item type
    Dewey Decimal Classification     Reference book Main Library Main Library Analytics 06/12/2023 Shroff Publisher 1280.00 Indian Book 005.74015 HUY 119114 06/12/2023 1600.00 Book

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