Guide intelligent data analysis di berthold michael (17 risultati)

Lingua: Inglese
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Guide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data (Texts in Computer Science)
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank
Lingua: Inglese
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Guide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data (Texts in Computer Science)
Borgelt, Christian,Berthold, Michael R.,Klawonn, Frank,HÃ ppner, Frank
Lingua: Inglese
Editore: Springer 2010
Serie: Texts in Computer Science, Libro 17 di 83. Libro 17 di 83 - Texts in Computer Science
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Guide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data
Berthold, Michael R./ Borgelt, Christian/ Hoppner, Frank/ Klawonn, Frank
Lingua: Inglese
Editore: Springer-Verlag New York Inc 2013
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Lingua: Inglese
Editore: Springer 2010
Serie: Texts in Computer Science, Libro 17 di 83. Libro 17 di 83 - Texts in Computer Science
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Lingua: Inglese
Editore: Springer 2012
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Taschenbuch. Condizione: Neu. Guide to Intelligent Data Analysis | How to Intelligently Make Sense of Real Data | Michael R. Berthold (u. a.) | Taschenbuch | Texts in Computer Science | xiii | Englisch | 2012 | Springer | EAN 9781447125723 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidel…berg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Lingua: Inglese
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now - at least in principle - solv…e any problem we are faced with so long as we only have enough data.Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable.To avoid the danger of 'drowning in information, but starving for knowledge' the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems.Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examplesto support pedagogical exposition.This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one's exploration of it.Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.

Guide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data (Texts in Computer Science) Berthold, Michael R.; Borgelt, Christian; Höppner, Frank and Klawonn, Frank
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank
Lingua: Inglese
Editore: Springer 2010
Serie: Texts in Computer Science, Libro 17 di 83. Libro 17 di 83 - Texts in Computer Science
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Guide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data (Texts in Computer Science)
Berthold, Michael R., Borgelt, Christian, Höppner, Frank, Kl
Lingua: Inglese
Editore: Springer 2010
Serie: Texts in Computer Science, Libro 17 di 83. Libro 17 di 83 - Texts in Computer Science
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Lingua: Inglese
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Lingua: Inglese
Editore: Springer London Sep 2012 2012
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now - at least in…principle - solve any problem we are faced with so long as we only have enough data.Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable.To avoid the danger of 'drowning in information, but starving for knowledge' the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems.Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examples to support pedagogical exposition.This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one's exploration of it.Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany. 408 pp. Englisch.

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Editore: Springer 2012
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Condizione: New. Print on Demand pp. 410 141 Illus. (78 Col.).

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Condizione: New. PRINT ON DEMAND pp. 410.

Lingua: Inglese
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a broad-range of perspectives on data analysis, providing readers with a comprehensive account of the fieldFocuses on the practical aspects as well as presenting the theory comprehensivelyA special emphasis…is given to put on pointing out the pitfa.

Lingua: Inglese
Editore: Springer, Springer Sep 2012 2012
Serie: Texts in Computer Science, Libro 17 di 83. Libro 17 di 83 - Texts in Computer Science
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now ¿ at least in prin…ciple ¿ solve any problem we are faced with so long as we only have enough data.Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable.To avoid the danger of ¿drowning in information, but starving for knowledge¿ the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems.Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examplesto support pedagogical exposition.This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one¿s exploration of it.Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 408 pp. Englisch.