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

More books from Springer International Publishing

Cover of the book A How To Guide For Medical Students by
Cover of the book Environmental Indicators in Metal Mining by
Cover of the book Digital Dilemmas by
Cover of the book Swarm Intelligence by
Cover of the book Inductive Logic Programming by
Cover of the book Companion Technology by
Cover of the book Divided Loyalties? Pushing the Boundaries of Gender and Lay Roles in the Catholic Church, 1534-1829 by
Cover of the book Non-Neuronal Mechanisms of Brain Damage and Repair After Stroke by
Cover of the book Indigenous Peoples' Cultural Property Claims by
Cover of the book Theory and Practice of Climate Adaptation by
Cover of the book Methods of Solving Complex Geometry Problems by
Cover of the book Cycles in US Foreign Policy since the Cold War by
Cover of the book Universal Access in Human–Computer Interaction. Designing Novel Interactions by
Cover of the book E-Learning Practice in Higher Education: A Mixed-Method Comparative Analysis by
Cover of the book Natural Polymers by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy