Data Science on the Google Cloud Platform: Implementing End-To-End Real-Time Data Pipelines: From Ingest to Machine Learning - Softcover

Lakshmanan, Valliappa

 
9781098118952: Data Science on the Google Cloud Platform: Implementing End-To-End Real-Time Data Pipelines: From Ingest to Machine Learning
Softcover
ISBN 10: 1098118952 ISBN 13: 9781098118952
Verlag: O'Reilly Media, 2022

Inhaltsangabe

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

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

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, using statistical and machine learning methods and tools on GCP.

Through the course of this updated second edition, 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:

  • 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

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
O'Reilly Media
Erscheinungsdatum
2022
Sprache
Englisch
ISBN 10 
1098118952
ISBN 13 
9781098118952
Einband
Taschenbuch
Auflage
2
Anzahl der Seiten
459
Kontakt zum Hersteller
O'Reilly
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