Data Science on the Google Cloud Platform

Data Science on the Google Cloud Platform

Implementing End-to-end Real-time Data Pipelines: From Ingest to Machine Learning

Book - 2018 | First edition.
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Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you'll work through a sample business decision by employing a variety of data science approaches.

Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science.

You'll learn how to:

Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines
Publisher: Sebastopol, CA : O'Reilly, 2018.
Edition: First edition.
ISBN: 9781491974568
Branch Call Number: 004.33 Lak
Characteristics: xiv, 393 pages : illustrations ; 24 cm

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