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Data Science on the Google Cloud Platform - Implementing end-to-end real-time data pipelines: from ingest to machine learning (Paperback) Loot Price: R1,076
Discovery Miles 10 760
You Save: R512 (32%)
Data Science on the Google Cloud Platform - Implementing end-to-end real-time data pipelines: from ingest to machine learning...

Data Science on the Google Cloud Platform - Implementing end-to-end real-time data pipelines: from ingest to machine learning (Paperback)

Valliappa Lakshmanan

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List price R1,588 Loot Price R1,076 Discovery Miles 10 760 | Repayment Terms: R101 pm x 12* You Save R512 (32%)

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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

General

Imprint: O'Reilly Media
Country of origin: United States
Release date: 2018
Authors: Valliappa Lakshmanan
Dimensions: 237 x 181 x 22mm (L x W x T)
Format: Paperback
Pages: 400
ISBN-13: 978-1-4919-7456-8
Categories: Books > Computing & IT > Computer communications & networking > General
Books > Computing & IT > Applications of computing > Databases > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN: 1-4919-7456-7
Barcode: 9781491974568

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