Data Science on the Google Cloud Platform PDF
by Valliappa Lakshmanan
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Description
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
Information
-
Download - Immediately Available
- Format:PDF
- Pages:462 pages
- Publisher:O'Reilly Media
- Publication Date:29/03/2022
- Category:
- ISBN:9781098118921
Other Formats
- Paperback / softback from £50.49
- EPUB from £38.39
Information
-
Download - Immediately Available
- Format:PDF
- Pages:462 pages
- Publisher:O'Reilly Media
- Publication Date:29/03/2022
- Category:
- ISBN:9781098118921
