Data Science on the Google Cloud Platform : Implementing end-to-end real-time data pipelines: from ingest to machine learning Paperback / softback
by Valliappa Lakshmanan
Paperback / softback
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Description
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
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Unavailable
- Format:Paperback / softback
- Pages:400 pages
- Publisher:O'Reilly Media, Inc, USA
- Publication Date:08/01/2018
- Category:
- ISBN:9781491974568
Other Formats
- Paperback / softback from £38.82
Information
-
Unavailable
- Format:Paperback / softback
- Pages:400 pages
- Publisher:O'Reilly Media, Inc, USA
- Publication Date:08/01/2018
- Category:
- ISBN:9781491974568