Authors:
- An essential introductory book on innovation, big data, and data science from a business perspective
- Provides a first read and point of departure for executives who want to keep pace with the breakthroughs introduced by new analytical techniques and tremendous amounts of data
- Addresses recent advances in machine learning, neuroscience, and artificial intelligence
Part of the book series: Studies in Big Data (SBD, volume 50)
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Table of contents (16 chapters)
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Front Matter
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Back Matter
About this book
This book reflects the author’s years of hands-on experience as an academic and practitioner. It is primarily intended for executives, managers and practitioners who want to redefine the way they think about artificial intelligence (AI) and other exponential technologies. Accordingly the book, which is structured as a collection of largely self-contained articles, includes both general strategic reflections and detailed sector-specific information. More concretely, it shares insights into what it means to work with AI and how to do it more efficiently; what it means to hire a data scientist and what new roles there are in the field; how to use AI in specific industries such as finance or insurance; how AI interacts with other technologies such as blockchain; and, in closing, a review of the use of AI in venture capital, as well as a snapshot of acceleration programs for AI companies.
Authors and Affiliations
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Department of Management, Ca’ Foscari University, Venice, Italy
Francesco Corea
Bibliographic Information
Book Title: An Introduction to Data
Book Subtitle: Everything You Need to Know About AI, Big Data and Data Science
Authors: Francesco Corea
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-3-030-04468-8
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-04467-1Published: 10 December 2018
eBook ISBN: 978-3-030-04468-8Published: 27 November 2018
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: XV, 131
Topics: Computational Intelligence, Big Data, Big Data/Analytics, Artificial Intelligence, Mathematical Models of Cognitive Processes and Neural Networks