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001			22938546
003			OSt
005			20240224162538.0
008			230124s2022 mau 000 0 eng d
010			_a 2022439566
015			_aGBC244268 _2bnb
016	7		_a020518055 _2Uk
020			_a9781098118952 _q(pbk.)
020			_a1098118952
035			_a(OCoLC)on1308488176
040			_aUKMGB _beng _cUKMGB _erda _dOCLCO _dUKMGB _dOCLCF _dTOH _dIVV _dNVC _dDLC
042			_alccopycat
050	0	0	_aQA76.585 _b.L35 2022
082	0	4	_a004.6782 LAK _223
092			_20
100	1		_aLakshmanan, Valliappa, _eauthor.
245	1	0	_aData science on the Google Cloud Platform : _bimplementing end-to-end real-time data pipelines : from ingest to machine learning / _cValliappa Lakshmanan.
250			_aSecond edition.
264		1	_aCambridge : _bO'Reilly, _c2022.
300			_axvii, 440 pages : _b illustrations ; _c24 cm.
336			_atext _2rdacontent
337			_aunmediated _2rdamedia
338			_avolume _2rdacarrier
500			_aPrevious edition: Sebastopol: O'Reilly, 2018.
504			_aIncludes bibliographical references and index.
520			_aLearn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines.
650		0	_aCloud computing.
650		0	_aComputing platforms.
650		6	_aInfonuagique.
650		6	_aPlateformes (Informatique)
650		7	_aCloud computing. _2fast _0(OCoLC)fst01745899
650		7	_aComputing platforms. _2fast _0(OCoLC)fst01893329
887			_2CamTech Library
906			_a7 _bcbc _ccopycat _d2 _encip _f20 _gy-gencatlg
942			_2ddc _cBK _n0
999			_c1479 _d1479