MARC Record from marc_openlibraries_sanfranciscopubliclibrary

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001 ocn966394369
003 OCoLC
005 20180123025210.0
008 161216s2017 caua 001 0 eng d
019 $a966609024
020 $a1491974567
020 $a9781491974568
035 $a(OCoLC)966394369$z(OCoLC)966609024
037 $bOreilly & Associates Inc, C/O Ingram Pub Services 1 Ingram Blvd, LA Vergne, TN, USA, 37086$nSAN 631-8673
040 $aYDX$beng$cYDX$dBDX$dBTCTA$dGK8$dSFR
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100 1 $aLakshmanan, Valliappa,$eauthor.
245 10 $aData science on the Google cloud platform :$bimplementing end-to-end real-time data pipelines: from ingest to machine learning /$cValliappa Lakshmanan.
250 $aFirst edition.
264 1 $aSebastopol, CA :$bO'Reilly Media,$c2018.
300 $axiv, 393 pages :$billustrations ;$c24 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
338 $avolume$bnc$2rdacarrier
500 $aIncludes index.
520 $aLearn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You'll learn how to: Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines
610 20 $aGoogle (Firm)
630 00 $aGoogle Apps.
650 0 $aReal-time data processing.
650 0 $aCloud computing.
650 0 $aComputing platforms.
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938 $aBaker and Taylor$bBTCP$nBK0019997159
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