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Data science on the Google cloud platform implementing end-to-end real-time data pipelines: from ingest to machine learning

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 a...

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Bibliographic Details
Main Author: Lakshmanan, Valliappa
Format: eBook
Language:English
Published: Sebastopol, CA O'Reilly Media 2018
Edition:First edition
Subjects:
Computers / Computer Science / Bisacsh
Cloud Computing / Fast
Google (firm) / Fast
Infonuagique
Computers / Hardware / General / Bisacsh
Computing Platforms / Fast
Computers / Data Processing / Bisacsh
Computers / Reference / Bisacsh
Real-time Data Processing / Http://id.loc.gov/authorities/subjects/sh85111765
Temps Réel (informatique)
Computing Platforms / Http://id.loc.gov/authorities/subjects/sh2011003111
Cloud Computing / Http://id.loc.gov/authorities/subjects/sh2008004883
Computers / Computer Literacy / Bisacsh
Real-time Data Processing / Fast
Plateformes (informatique)
Google (firm) / Http://id.loc.gov/authorities/names/no00095539
Computers / Machine Theory / Bisacsh
Computers / Information Technology / Bisacsh
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • Making better decisions based on data
  • Ingesting data into the cloud
  • Creating compelling dashboards
  • Streaming data: publication and ingest
  • Interactive data exploration
  • Bayes classifier on cloud dataproc
  • Machine learning: logistic regression on Spark
  • Time-windowed aggregate features
  • Machine learning classifier using TensorFlow
  • Real-time machine learning

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