Machine Learning Paradigms: Advances in Data Analytics

Author:   George A. Tsihrintzis ,  Dionisios N. Sotiropoulos ,  Lakhmi C. Jain
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2019
Volume:   149
ISBN:  

9783319940298


Pages:   370
Publication Date:   12 July 2018
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Machine Learning Paradigms: Advances in Data Analytics


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Overview

This book explores some of the emerging scientific and technological areas in which the need for data analytics arises and is likely to play a significant role in the years to come. At the dawn of the 4th Industrial Revolution, data analytics is emerging as a force that drives towards dramatic changes in our daily lives, the workplace and human relationships. Synergies between physical, digital, biological and energy sciences and technologies, brought together by non-traditional data collection and analysis, drive the digital economy at all levels and offer new, previously-unavailable opportunities. The need for data analytics arises in most modern scientific disciplines, including engineering; natural-, computer- and information sciences; economics; business; commerce; environment; healthcare; and life sciences. Coming as the third volume under the general title MACHINE LEARNING PARADIGMS, the book includes an editorial note (Chapter 1) and an additional 12 chapters, and is divided into five parts: (1) Data Analytics in the Medical, Biological and Signal Sciences, (2) Data Analytics in Social Studies and Social Interactions, (3) Data Analytics in Traffic, Computer and Power Networks, (4) Data Analytics for Digital Forensics, and (5) Theoretical Advances and Tools for Data Analytics. This research book is intended for both experts/researchers in the field of data analytics, and readers working in the fields of artificial and computational intelligence as well as computer science in general who wish to learn more about the field of data analytics and its applications. An extensive list of bibliographic references at the end of each chapter guides readers to probe further into the application areas of interest to them.

Full Product Details

Author:   George A. Tsihrintzis ,  Dionisios N. Sotiropoulos ,  Lakhmi C. Jain
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2019
Volume:   149
Weight:   0.746kg
ISBN:  

9783319940298


ISBN 10:   3319940295
Pages:   370
Publication Date:   12 July 2018
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Reviews

It contains interesting work on machine learning in the medical domain. ... it is an interesting collection of machine learning applications across multiple domains. It may be of interest to readers working in one of the discussed areas. (K. Waldhoer, Computing Reviews, January, 2019)


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