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010   $a3-030-04468-8
024 7 $a10.1007/978-3-030-04468-8
035   $a(CKB)4100000007181094
035   $a(MiAaPQ)EBC5606681
035   $a(DE-He213)978-3-030-04468-8
035   $a(PPN)243767528
035   $a(EXLCZ)994100000007181094
100   $a20181127d2019      u|             0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 13$aAn Introduction to Data$b[electronic resource] $eEverything You Need to Know About AI, Big Data and Data Science /$fby Francesco Corea
205   $a1st ed. 2019.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019.
215   $a1 online resource (131 pages)
225 1 $aStudies in Big Data,$x2197-6503 ;$v50
311   $a3-030-04467-X 
327   $aIntroduction 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.
330   $aThis book reflects the author?s years of hands-on experience as an academic and practitioner. It is primarily intended for executives, managers and practitioners who want to redefine the way they think about artificial intelligence (AI) and other exponential technologies. Accordingly the book, which is structured as a collection of largely self-contained articles, includes both general strategic reflections and detailed sector-specific information. More concretely, it shares insights into what it means to work with AI and how to do it more efficiently; what it means to hire a data scientist and what new roles there are in the field; how to use AI in specific industries such as finance or insurance; how AI interacts with other technologies such as blockchain; and, in closing, a review of the use of AI in venture capital, as well as a snapshot of acceleration programs for AI companies. .
410  0$aStudies in Big Data,$x2197-6503 ;$v50
606   $aComputational intelligence
606   $aBig data
606   $aArtificial intelligence
606   $aNeural networks (Computer science) 
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120
606   $aBig Data/Analytics$3https://scigraph.springernature.com/ontologies/product-market-codes/522070
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aMathematical Models of Cognitive Processes and Neural Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/M13100
615  0$aComputational intelligence.
615  0$aBig data.
615  0$aArtificial intelligence.
615  0$aNeural networks (Computer science) .
615 14$aComputational Intelligence.
615 24$aBig Data.
615 24$aBig Data/Analytics.
615 24$aArtificial Intelligence.
615 24$aMathematical Models of Cognitive Processes and Neural Networks.
676   $a006.3019
700   $aCorea$b Francesco$4aut$4http://id.loc.gov/vocabulary/relators/aut$0761218
906   $aBOOK
912   $a9910483395803321
996   $aAn Introduction to Data$92853750
997   $aUNINA