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    Unicorns Among Us: Understanding The High Priests of Data Science (New Street Data Science Basics Book 3) (English Edition)

    Por Lars Nielsen

    Sobre

    Data scientists – the so-called "high-priests" of big data – combine unique and esoteric skills. Part intuitive artist, part statistical modeler, part programmer, the practitioner of this new art of research must be able to detect and make sense out of patterns hidden within millions upon millions of pieces of constantly streaming, completely unstructured data.

    He or she must also must be able to smooth and clean the data, ask the right questions about that data, make valid inferences from the data as to how consumers and markets behave, and finally, create statistical models with which to pinpoint behavioral triggers which prove or disprove their theories.

    Jonathan Goldman, who administered the data science team behind LinkedIn's highly successful “People You May Know” button, notes that data scientists are sometimes referred to as “unicorns” simply because the combination of skills and talents required to do their job is so rare and hard to find.

    In UNICORNS AMONG US, Lars Nielsen lays out the brief history of data science as a craft. He as well explores the evolution of the role of the data scientist, and lays out the qualifications, the tools, the techniques and the training involved in the practice of this arcane discipline.

    Nielsen's book will prove indispensable for anyone contemplating a career in this lucrative area, as well as anyone tasked to work with or manage a data science project or team.


    CONTENTS: High Priests * Part Analyst, Part Inspired Artist * Data Wrangling * The Human Factor vs. The Machine Factor * The Dats Scientist's Shifting Role * A Cool Sub-Niche: Crowd Science * The Data Scientist's Most Important Tool: Hadoop * A Fantastic Kind of Abstraction: The Origins of Hadoop * A Platform is Born * Hadoop Grows Up * A Cautionary Summing Up


    ABOUT THE AUTHOR: Lars Nielsen's bestselling books include COMPUTING: A BUSINESS HISTORY and A SIMPLE INTRODUCTION TO DATA SCIENCE.
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