Feature Store for Machine Learning : (Record no. 8362)
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fixed length control field | 04173cam a22004337a 4500 |
001 - CONTROL NUMBER | |
control field | on1323251096 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | OCoLC |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20241121073031.0 |
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION | |
fixed length control field | m d |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
fixed length control field | cr cnu---unuuu |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 220625s2022 enk o 000 0 eng d |
040 ## - CATALOGING SOURCE | |
Original cataloging agency | EBLCP |
Language of cataloging | eng |
Description conventions | pn |
Transcribing agency | EBLCP |
Modifying agency | ORMDA |
-- | OCLCF |
-- | OCLCQ |
-- | N$T |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 1803245980 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9781803245980 |
Qualifying information | (electronic bk.) |
035 ## - SYSTEM CONTROL NUMBER | |
System control number | 3296295 |
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035 ## - SYSTEM CONTROL NUMBER | |
System control number | (OCoLC)1323251096 |
037 ## - SOURCE OF ACQUISITION | |
Stock number | 9781803230061 |
Source of stock number/acquisition | O'Reilly Media |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | Q325.5 |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.3/1 |
Edition number | 23/eng/20220706 |
049 ## - LOCAL HOLDINGS (OCLC) | |
Holding library | MAIN |
100 1# - MAIN ENTRY--PERSONAL NAME | |
Personal name | Kumar M. J., Jayanth. |
9 (RLIN) | 20206 |
245 10 - TITLE STATEMENT | |
Title | Feature Store for Machine Learning : |
Remainder of title | Curate, Discover, Share and Serve ML Features at Scale. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Place of publication, distribution, etc | Birmingham : |
Name of publisher, distributor, etc | Packt Publishing, Limited, |
Date of publication, distribution, etc | 2022. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | 1 online resource (281 pages) |
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-- | txt |
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-- | computer |
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-- | online resource |
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-- | Print version record. |
520 ## - SUMMARY, ETC. | |
Summary, etc | Learn how to leverage feature stores to make the most of your machine learning models Key Features Understand the significance of feature stores in the ML life cycle Discover how features can be shared, discovered, and re-used Learn to make features available for online models during inference Book Description Feature store is one of the storage layers in machine learning (ML) operations, where data scientists and ML engineers can store transformed and curated features for ML models. This makes them available for model training, inference (batch and online), and reuse in other ML pipelines. Knowing how to utilize feature stores to their fullest potential can save you a lot of time and effort, and this book will teach you everything you need to know to get started. Feature Store for Machine Learning is for data scientists who want to learn how to use feature stores to share and reuse each other's work and expertise. You'll be able to implement practices that help in eliminating reprocessing of data, providing model-reproducible capabilities, and reducing duplication of work, thus improving the time to production of the ML model. While this ML book offers some theoretical groundwork for developers who are just getting to grips with feature stores, there's plenty of practical know-how for those ready to put their knowledge to work. With a hands-on approach to implementation and associated methodologies, you'll get up and running in no time. By the end of this book, you'll have understood why feature stores are essential and how to use them in your ML projects, both on your local system and on the cloud. What you will learn Understand the significance of feature stores in a machine learning pipeline Become well-versed with how to curate, store, share and discover features using feature stores Explore the different components and capabilities of a feature store Discover how to use feature stores with batch and online models Accelerate your model life cycle and reduce costs Deploy your first feature store for production use cases Who this book is for If you have a solid grasp on machine learning basics, but need a comprehensive overview of feature stores to start using them, then this book is for you. Data/machine learning engineers and data scientists who build machine learning models for production systems in any domain, those supporting data engineers in productionizing ML models, and platform engineers who build data science (ML) platforms for the organization will also find plenty of practical advice in the later chapters of this book. |
590 ## - LOCAL NOTE (RLIN) | |
Local note | Added to collection customer.56279.3 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Machine learning. |
9 (RLIN) | 2890 |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Machine learning. |
Source of heading or term | fast |
-- | (OCoLC)fst01004795 |
9 (RLIN) | 2890 |
655 #4 - INDEX TERM--GENRE/FORM | |
Genre/form data or focus term | Electronic books. |
9 (RLIN) | 3907 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Print version: |
Main entry heading | J, Jayanth Kumar M. |
Title | Feature Store for Machine Learning. |
Place, publisher, and date of publication | Birmingham : Packt Publishing, Limited, �2022 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Materials specified | EBSCOhost |
Uniform Resource Identifier | <a href="https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3296295">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3296295</a> |
938 ## - | |
-- | ProQuest Ebook Central |
-- | EBLB |
-- | EBL7001663 |
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-- | EBSCOhost |
-- | EBSC |
-- | 3296295 |
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-- | 92 |
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