000			04173cam a22004337a 4500
001			on1323251096
003			OCoLC
005			20241121073031.0
006			m d
007			cr cnu---unuuu
008			220625s2022 enk o 000 0 eng d
040			_aEBLCP _beng _epn _cEBLCP _dORMDA _dOCLCF _dOCLCQ _dN$T
020			_a1803245980
020			_a9781803245980 _q(electronic bk.)
035			_a3296295 _b(N$T)
035			_a(OCoLC)1323251096
037			_a9781803230061 _bO'Reilly Media
050		4	_aQ325.5
082	0	4	_a006.3/1 _223/eng/20220706
049			_aMAIN
100	1		_aKumar M. J., Jayanth. _920206
245	1	0	_aFeature Store for Machine Learning : _bCurate, Discover, Share and Serve ML Features at Scale.
260			_aBirmingham : _bPackt Publishing, Limited, _c2022.
300			_a1 online resource (281 pages)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
588	0		_aPrint version record.
520			_aLearn 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			_aAdded to collection customer.56279.3
650		0	_aMachine learning. _92890
650		7	_aMachine learning. _2fast _0(OCoLC)fst01004795 _92890
655		4	_aElectronic books. _93907
776	0	8	_iPrint version: _aJ, Jayanth Kumar M. _tFeature Store for Machine Learning. _dBirmingham : Packt Publishing, Limited, �2022
856	4	0	_3EBSCOhost _uhttps://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3296295
938			_aProQuest Ebook Central _bEBLB _nEBL7001663
938			_aEBSCOhost _bEBSC _n3296295
994			_a92 _bN$T
999			_c8362 _d8362