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

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

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

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

Category

Data Science

Cloud Computing

Author

Valliappa Lakshmanan

Publication

OReilly Media

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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

'

Download pdf

ISBN-10

1098118952

ISBN-13

978-1098118952

Publisher

OReilly Media

Price

50.99

File Type

PDF

Page No.

459

Valliappa Lakshmanan

Valliappa Lakshmanan

Lak is Head for Data Analytics and AI Solutions on Google Cloud. His team builds software solutions ...

About the Author

Valliappa (Lak) Lakshmanan is the director of analytics and AI solutions at Google Cloud, where he leads a team building cross-industry solutions to business problems. His mission is to democratize machine learning so that it can be done by anyone anywhere. Lak is the author or coauthor of Practical Machine Learning for Computer Vision, Machine Learning Design Patterns, Data Governance The Definitive Guide, Google BigQuery The Definitive Guide, and Data Science on the Google Cloud Platform.

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