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

Lakshmanan, Valliappa

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

Über diesen Titel

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

Details zur Ausgabe

• 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; https://oreilly.com; ; 1005 Gravenstein Highway North; Sebastopol; CA; 95472; USA
• Verantwortliche Person: preigu; mail@preigu.de; ; Lengericher Landstr. 19; Osnabrück; 49078; Deutschland