Description

Book Synopsis

Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets.

The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions.

What You''ll Learn
  • Become fluent in the essential concepts and terminology of data science and data engineering 
  • Build and use a technology stack that meets industry criteria
  • Master the methods for retrieving actionable business knowledge
  • Coordinate the handling of

    Table of Contents


Practical Data Science

    Product form

    A Paperback by Andreas Francois Vermeulen

    £999.99

    Includes FREE delivery

    Out of stock

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      Book details

      Publisher Springer Nature
      Published 22 January 2018
      ISBN-13 9781484230534
      978-1484230534
      ISBN-10 1484230531
      Also in:
      Business mathematics and systems Expert systems / knowledge-based systems

      Description

      Book Synopsis

      Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets.

      The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions.

      What You''ll Learn
      • Become fluent in the essential concepts and terminology of data science and data engineering 
      • Build and use a technology stack that meets industry criteria
      • Master the methods for retrieving actionable business knowledge
      • Coordinate the handling of

        Table of Contents


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