Said A. et al. (eds.) Data Science in Practice

Springer, 2018. — 199 p. — ISBN: 3319975552.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.Alan Said and Vicenç Torra
Data Science: An Introduction
Concepts
Vicenç Torra, Alexander Karlsson, H. Joe Steinhauer and Stefan Berglund
Artificial Intelligence
Denio Duarte and Niclas Ståhl
Machine Learning: A Concise Overview
Application Domains
H. Joe Steinhauer and Alexander Karlsson
Information Fusion
Alejandro Bellogín and Alan Said
Information Retrieval and Recommender Systems
Carl Anderson
Business Intelligence
Tools
Vicenç Torra, Guillermo Navarro-Arribas and Klara Stokes
Data Privacy
Juhee Bae, Göran Falkman, Tove Helldin and Maria Riveiro
Visual Data Analysis
Juhee Bae, Alexander Karlsson, Jonas Mellin, Niclas Ståhl and Vicenç Torra
Complex Data Analysis
lio Ventocilla
Big Data Programming with Apache Spark