Data science on the Google Cloud Platform : implementing end-to-end real-time data pipelines : from ingest to machine learning

書誌事項

Data science on the Google Cloud Platform : implementing end-to-end real-time data pipelines : from ingest to machine learning

Valliappa Lakshmanan

O'Reilly, 2022

2nd ed

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注記

First ed.: 2018

内容説明・目次

内容説明

Learn 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

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詳細情報

  • NII書誌ID(NCID)
    BC16346454
  • ISBN
    • 9781098118952
  • 出版国コード
    us
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    Sebastopol, Calif.
  • ページ数/冊数
    xvii, 440 p.
  • 大きさ
    24 cm
  • 分類
  • 件名
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