Data science on the Google cloud platform
Subtitle: implementing end-to-end real-time data pipelines: from ingest to machine learning
By: Valliappa Lakshmanan
Edition: First edition.
Publisher: O'Reilly Media, Incorporated
Published: 2017
Language: eng
Number of pages: 393
ISBN-13: 9781491974568
Subjects: Real-time data processing; Google (Firm); Google Apps; Cloud computing; Computing platforms
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
Notes: Includes index.