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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
This is a digital product.
Additional ISBNs
9781098118921
Data Science on the Google Cloud Platform 2nd Edition is written by Valliappa Lakshmanan and published by O’Reilly Media. The Digital and eTextbook ISBNs for Data Science on the Google Cloud Platform are 9781098118914, 109811891X and the print ISBNs are 9781098118952, 1098118952. Additional ISBNs for this eTextbook include 9781098118921.
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