Data Science on the Google Cloud Platform

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

By Valliappa Lakshmanan

cover image of Data Science on the Google Cloud Platform

Sign up to save your library

With an OverDrive account, you can save your favorite libraries for at-a-glance information about availability. Find out more about OverDrive accounts.

   Not today

Find this title in Libby, the library reading app by OverDrive.

Download Libby on the App Store Download Libby on Google Play

Search for a digital library with this title

Title found at these libraries:

Library Name Distance
Loading...

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
  • Data Science on the Google Cloud Platform