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Big data analytics
Titre : Big data analytics : handbook of statistics volume 33 Type de document : texte imprimé Auteurs : Venugopal Govindaraju, Editeur scientifique ; Vijay V. Raghavan, Editeur scientifique ; Calyampudi Radhakrishna Rao (1920-....), Editeur scientifique Editeur : Amsterdam : North-Holland Année de publication : cop. 2015 Autre Editeur : Elsevier Collection : Handbook of Statistics num. 33 Importance : 1 ressource dématérialisée ISBN/ISSN/EAN : 978-0-444-63492-4 Note générale : Bibliogr. en fin de chapitres. Index Langues : Anglais (eng) Mots-clés : Big data analytics handbook statistics Index. décimale : 515 Résumé : While the term Big Data is open to varying interpretation, it is quite clear that the Volume, Velocity, and Variety (3Vs) of data have impacted every aspect of computational science and its applications. The volume of data is increasing at a phenomenal rate and a majority of it is unstructured. With big data, the volume is so large that processing it using traditional database and software techniques is difficult, if not impossible. The drivers are the ubiquitous sensors, devices, social networks and the all-pervasive web. Scientists are increasingly looking to derive insights from the massive quantity of data to create new knowledge. In common usage, Big Data has come to refer simply to the use of predictive analytics or other certain advanced methods to extract value from data, without any required magnitude thereon. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. While there are challenges, there are huge opportunities emerging in the fields of Machine Learning, Data Mining, Statistics, Human-Computer Interfaces and Distributed Systems to address ways to analyze and reason with this data. The edited volume focuses on the challenges and opportunities posed by "Big Data" in a variety of domains and how statistical techniques and innovative algorithms can help glean insights and accelerate discovery. Big data has the potential to help companies improve operations and make faster, more intelligent decisions.
Review of big data research challenges from diverse areas of scientific endeavor
Rich perspective on a range of data science issues from leading researchers
Insight into the mathematical and statistical theory underlying the computational methods used to address big data analytics problems in a variety of domainsBig data analytics : handbook of statistics volume 33 [texte imprimé] / Venugopal Govindaraju, Editeur scientifique ; Vijay V. Raghavan, Editeur scientifique ; Calyampudi Radhakrishna Rao (1920-....), Editeur scientifique . - Amsterdam : North-Holland : [S.l.] : Elsevier, cop. 2015 . - 1 ressource dématérialisée. - (Handbook of Statistics; 33) .
ISBN : 978-0-444-63492-4
Bibliogr. en fin de chapitres. Index
Langues : Anglais (eng)
Mots-clés : Big data analytics handbook statistics Index. décimale : 515 Résumé : While the term Big Data is open to varying interpretation, it is quite clear that the Volume, Velocity, and Variety (3Vs) of data have impacted every aspect of computational science and its applications. The volume of data is increasing at a phenomenal rate and a majority of it is unstructured. With big data, the volume is so large that processing it using traditional database and software techniques is difficult, if not impossible. The drivers are the ubiquitous sensors, devices, social networks and the all-pervasive web. Scientists are increasingly looking to derive insights from the massive quantity of data to create new knowledge. In common usage, Big Data has come to refer simply to the use of predictive analytics or other certain advanced methods to extract value from data, without any required magnitude thereon. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. While there are challenges, there are huge opportunities emerging in the fields of Machine Learning, Data Mining, Statistics, Human-Computer Interfaces and Distributed Systems to address ways to analyze and reason with this data. The edited volume focuses on the challenges and opportunities posed by "Big Data" in a variety of domains and how statistical techniques and innovative algorithms can help glean insights and accelerate discovery. Big data has the potential to help companies improve operations and make faster, more intelligent decisions.
Review of big data research challenges from diverse areas of scientific endeavor
Rich perspective on a range of data science issues from leading researchers
Insight into the mathematical and statistical theory underlying the computational methods used to address big data analytics problems in a variety of domainsRéservation
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Code-barres Cote Support Localisation Section Disponibilité fsei12053 515-208.1 Ouvrage Faculté des Sciences Exactes et Informatique 500 - Sciences de la nature et Mathématiques Disponible Perry's Chemical Engineers' Handbook / Robert H. Perry
Titre : Perry's Chemical Engineers' Handbook Type de document : texte imprimé Auteurs : Robert H. Perry, Auteur Mention d'édition : 5 em ed. Editeur : McGraw-Hill Inc.,US Année de publication : 1973 Importance : Relié 2240 p. Langues : Français (fre) Mots-clés : Handbook Chemical Engineer Index. décimale : 660 Perry's Chemical Engineers' Handbook [texte imprimé] / Robert H. Perry, Auteur . - 5 em ed. . - [S.l.] : McGraw-Hill Inc.,US, 1973 . - Relié 2240 p.
Langues : Français (fre)
Mots-clés : Handbook Chemical Engineer Index. décimale : 660 Réservation
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Code-barres Cote Support Localisation Section Disponibilité fsei14181 660-20.1 Ouvrage Faculté des Sciences Exactes et Informatique 600 - Technologie (Sciences appliquées) Disponible fsei14182 660-20.2 Ouvrage Faculté des Sciences Exactes et Informatique 600 - Technologie (Sciences appliquées) Disponible fsei14183 660-20.3 Ouvrage Faculté des Sciences Exactes et Informatique 600 - Technologie (Sciences appliquées) Disponible