Data Science and Digital Business
Editat de Fausto Pedro García Márquez, Benjamin Leven Limba Engleză Hardback – 16 ian 2019
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Specificații
ISBN-13: 9783319956503
ISBN-10: 3319956507
Pagini: 302
Ilustrații: VIII, 316 p. 117 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.63 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
ISBN-10: 3319956507
Pagini: 302
Ilustrații: VIII, 316 p. 117 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.63 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
Cuprins
Advanced Regression Models in Data Science.- Data Science Method in Analysis of Flood Risk in Mississippi Gulf Coast Area.- An efficient bundle-like algorithm for data-driven multi-objective bi-level signal design for traffic networks with hazardous material transportation.- Deploying a scalable Data Science environment using Docker.- Data Science and Conversational Interfaces: A new revolution in Digital Business.- After 2017: Managers Exit and Banks Arise.
Recenzii
“If you have an interest in analytics and visualization, and would like to review several applications of classification models, you may find it an interesting read.” (Robert M. Lynch, Computing Reviews, September 09, 2019)
Notă biografică
Dr. Fausto Pedro García Márquez completed his European Doctorate in Engineering at the University of Castilla-La Mancha (UCLM) in 2004. He received his Engineering degree from the University of Murcia, Spain in 1998, and his Technical Engineering degree at UCLM in 1995 and degree in Business Administration and Management at UCLM in 2006. He has also served as Technician in Labor Risk Prevention by UCLM (2000) and Transport Specialist at the Polytechnic University of Madrid, Spain (2001). He was a Senior Manager at Accenture in 2013/2014, and is currently a Senior Lecturer (Full Professor accredited) at UCLM, an Honorary Senior Research Fellow at the University of Birmingham, UK, a Lecturer at the Instituto Europeo de Postgrado and Director of the Ingenium Research Group. He has been the principal investigator in 3 European Projects and 60 national and corporate research projects. He holds international and national patents, and has authored more than 110 international papers and 10books. His work has been recognized with 3 International Awards in Engineering Management and Management Science.
Dr. Benjamin Lev is a Professor and Head of Decision Sciences at LeBow College of Business. He holds a PhD in Operations Research from Case Western Reserve University. Prior to joining Drexel University, Dr. Lev held academic and administrative positions at Temple University, the University of Michigan-Dearborn and Worcester Polytechnic Institute. He is the Editor-in-Chief of OMEGA – The International journal of Management Science, the Co-Editor-in-Chief of the International Journal of Management Science and Engineering Management, and serves on several other journal editorial boards. He has published over ten books and numerous articles, and has organized many national and international conferences.
Dr. Benjamin Lev is a Professor and Head of Decision Sciences at LeBow College of Business. He holds a PhD in Operations Research from Case Western Reserve University. Prior to joining Drexel University, Dr. Lev held academic and administrative positions at Temple University, the University of Michigan-Dearborn and Worcester Polytechnic Institute. He is the Editor-in-Chief of OMEGA – The International journal of Management Science, the Co-Editor-in-Chief of the International Journal of Management Science and Engineering Management, and serves on several other journal editorial boards. He has published over ten books and numerous articles, and has organized many national and international conferences.
Textul de pe ultima copertă
This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.
Caracteristici
Helps readers understand the premises of digital science Covers interdisciplinary aspects of data science Presents case studies with real-world examples from the digital business