Data Science on the Google Cloud Platform
Implementing End-to-end Real-time Data Pipelines: from Ingest to Machine Learning
Autor*in: Lakshmanan, Valliappa
Jahr: 2017
Sprache: Englisch
Umfang: 410 S.
Verfügbar
- Inhalt:
- 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
Titelinformationen
Titel: Data Science on the Google Cloud Platform
Autor*in: Lakshmanan, Valliappa
Verlag: Oreilly & Associates Inc
ISBN: 9781491974513
Kategorie: Sachmedien & Ratgeber, Computer & Internet, Allgemeines
Max. Ausleihdauer: 21 Tage