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Data Science on the Google Cloud Platform : Implementing End-To-End Real-Time Data Pipelines: from Ingest to Machine Learning by Valliappa Lakshmanan (2022, Trade Paperback)
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The product is a textbook titled "Data Science on the Google Cloud Platform: Implementing End-To-End Real-Time Data Pipelines from Ingest to Machine Learning" by Valliappa Lakshmanan. Published by O'Reilly Media, the textbook focuses on cloud computing, data modeling, and design, with an emphasis on data processing. With 459 pages, the trade paperback is written in English and provides a comprehensive guide on implementing real-time data pipelines on the Google Cloud Platform. It covers various aspects of data science and machine learning, making it a valuable resource for students and professionals in the field.
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About this product
Product Identifiers
PublisherO'reilly Media, Incorporated
ISBN-101098118952
ISBN-139781098118952
eBay Product ID (ePID)23057264474
Product Key Features
Number of Pages459 Pages
Publication NameData Science on the Google Cloud Platform : Implementing End-To-End Real-Time Data Pipelines: from Ingest to Machine Learning
LanguageEnglish
SubjectCloud Computing, Data Modeling & Design, General, Data Processing
Publication Year2022
TypeTextbook
Subject AreaMathematics, Computers
AuthorValliappa Lakshmanan
FormatTrade Paperback
Dimensions
Item Height1.1 in
Item Weight28.5 Oz
Item Length9.1 in
Item Width7 in
Additional Product Features
Edition Number2
Intended AudienceScholarly & Professional
LCCN2022-439566
Dewey Edition23
Dewey Decimal004.6782
SynopsisLearn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines
LC Classification NumberQA76.585
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