Data Science in Practice

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Business & Finance, Industries & Professions, Industries, General Computing
Cover of the book Data Science in Practice by , Springer International Publishing
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Author: ISBN: 9783319975566
Publisher: Springer International Publishing Publication: September 19, 2018
Imprint: Springer Language: English
Author:
ISBN: 9783319975566
Publisher: Springer International Publishing
Publication: September 19, 2018
Imprint: Springer
Language: English

This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and time again in the mainstream media. However, our understanding of what they actually mean often remains limited. This book provides a general overview of the terms and approaches used broadly in data science, and provides detailed information on the underlying theories, models, and application scenarios. Divided into three main parts, it addresses what data science is; how and where it is used; and how it can be implemented using modern open source software. The book offers an essential guide to modern data science for all students, practitioners, developers and managers seeking a deeper understanding of how various aspects of data science work, and of how they can be employed to gain a competitive advantage.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and time again in the mainstream media. However, our understanding of what they actually mean often remains limited. This book provides a general overview of the terms and approaches used broadly in data science, and provides detailed information on the underlying theories, models, and application scenarios. Divided into three main parts, it addresses what data science is; how and where it is used; and how it can be implemented using modern open source software. The book offers an essential guide to modern data science for all students, practitioners, developers and managers seeking a deeper understanding of how various aspects of data science work, and of how they can be employed to gain a competitive advantage.

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