105,65 €
117,39 €
-10% with code: EXTRA
Data Science on the Google Cloud Platform
Data Science on the Google Cloud Platform
105,65
117,39 €
  • We will send in 10–14 business days.
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…
117.39
  • SAVE -10% with code: EXTRA

Data Science on the Google Cloud Platform (e-book) (used book) | bookbook.eu

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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

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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

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