Data Science On The Google Cloud Platform, 2/e:

Implementing End-To-End Real-Time Data Pipelines: From Ingest To Machine Learning

Author: Valliappa Lakshmanan

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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
Author
Valliappa Lakshmanan
Binding
Paperback
Condition Type
New
Country Origin
India
Edition
2
Gift Wrap
Yes
Leadtime to ship in days (default)
Usually ships in 2 days
Page
440
Publisher
Shroff/O'Reilly
Year
2022
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