Data Science on the Google Cloud Platform
Implementing End-to-end Real-time Data Pipelines: from Ingest to Machine Learning
Person: Lakshmanan, Valliappa
Year: 2017
Language: English
Scope: 410 p.
Available
- Contents:
- 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
Title Information
Title: Data Science on the Google Cloud Platform
Person: Lakshmanan, Valliappa
Publisher : Oreilly & Associates Inc
ISBN: 9781491974513
Category: Non-Fiction & Guidebooks, Computer & Internet, General
Loan period: 21 days