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An introduction to data = everything...

Corea, Francesco.

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An introduction to data = everything you need to know about AI, big data and data science /

Record Type:	Electronic resources : Monograph/item
Title/Author:	An introduction to data/ by Francesco Corea.
Reminder of title:	everything you need to know about AI, big data and data science /
Author:	Corea, Francesco.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xv, 131 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction to Data -- Big Data Management: How Organizations Create and Implement Data Strategies -- Introduction to Artificial Intelligence -- AI Knowledge Map: how to classify AI technologies -- Advancements in the field -- AI Business Models -- Hiring a data scientist -- AI and Speech Recognition -- AI and Insurance -- AI and Financial Services -- AI and Blockchain -- New roles in AI -- AI and Ethics -- AI and Intellectual Property -- AI and Venture Capital -- A guide to AI accelerators and incubators.
Contained By:	Springer eBooks
Subject:	Big data. -
Online resource:	https://doi.org/10.1007/978-3-030-04468-8
ISBN:	9783030044688

An introduction to data = everything you need to know about AI, big data and data science /
Corea, Francesco.

An introduction to dataeverything you need to know about AI, big data and data science /[electronic resource] :by Francesco Corea. - Cham :Springer International Publishing :2019. - xv, 131 p. :ill., digital ;24 cm. - Studies in big data,v.502197-6503 ;. - Studies in big data ;v.50..

Introduction to Data -- Big Data Management: How Organizations Create and Implement Data Strategies -- Introduction to Artificial Intelligence -- AI Knowledge Map: how to classify AI technologies -- Advancements in the field -- AI Business Models -- Hiring a data scientist -- AI and Speech Recognition -- AI and Insurance -- AI and Financial Services -- AI and Blockchain -- New roles in AI -- AI and Ethics -- AI and Intellectual Property -- AI and Venture Capital -- A guide to AI accelerators and incubators.

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.

ISBN: 9783030044688

Standard No.: 10.1007/978-3-030-04468-8doiSubjects--Topical Terms:

2045508
Big data.

LC Class. No.: QA76.9.B45 / C67 2019

Dewey Class. No.: 005.7

An introduction to data = everything you need to know about AI, big data and data science /
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505 0 $a Introduction to Data -- Big Data Management: How Organizations Create and Implement Data Strategies -- Introduction to Artificial Intelligence -- AI Knowledge Map: how to classify AI technologies -- Advancements in the field -- AI Business Models -- Hiring a data scientist -- AI and Speech Recognition -- AI and Insurance -- AI and Financial Services -- AI and Blockchain -- New roles in AI -- AI and Ethics -- AI and Intellectual Property -- AI and Venture Capital -- A guide to AI accelerators and incubators.
520 $a 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.
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