Condition: Sehr gut. Zustand: Sehr gut | Seiten: 628 | Sprache: Englisch | Produktart: Bücher | Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.
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Taschenbuch. Condition: Neu. Data Mining for Scientific and Engineering Applications | R. L. Grossman (u. a.) | Taschenbuch | Massive Computing | xx | Englisch | 2001 | Springer | EAN 9781402001147 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Language: English
Published by Kluwer Academic Publishers, 2001
ISBN 10: 1402001142 ISBN 13: 9781402001147
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Condition: New. Illustrates the diversity of problems and application areas that can benefit from data mining, as well as issues and challenges that differentiate scientific data mining from its commercial counterpart. This book focuses on mining scientific data. It is suitable for students and researchers who are familiar with basic principles of data mining. Editor(s): Grossman, Robert L.; Kamath, Chandrika; Kegelmeyer, P.; Kumar, V. Series: Massive Computing. Num Pages: 605 pages, biography. BIC Classification: UN. Category: (G) General (US: Trade); (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 240 x 160 x 32. Weight in Grams: 1910. . 2001. Softcover reprint of the original 1st ed. 2001. Paperback. . . . .
Condition: New. pp. 632.
Language: English
Published by Kluwer Academic Publishers, 2001
ISBN 10: 1402001142 ISBN 13: 9781402001147
Seller: Kennys Bookstore, Olney, MD, U.S.A.
Condition: New. Illustrates the diversity of problems and application areas that can benefit from data mining, as well as issues and challenges that differentiate scientific data mining from its commercial counterpart. This book focuses on mining scientific data. It is suitable for students and researchers who are familiar with basic principles of data mining. Editor(s): Grossman, Robert L.; Kamath, Chandrika; Kegelmeyer, P.; Kumar, V. Series: Massive Computing. Num Pages: 605 pages, biography. BIC Classification: UN. Category: (G) General (US: Trade); (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 240 x 160 x 32. Weight in Grams: 1910. . 2001. Softcover reprint of the original 1st ed. 2001. Paperback. . . . . Books ship from the US and Ireland.
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.
Language: English
Published by Springer US, Springer US, 2001
ISBN 10: 1402000332 ISBN 13: 9781402000331
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientist.
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientist.
Language: English
Published by Springer US, Springer US Okt 2001, 2001
ISBN 10: 1402001142 ISBN 13: 9781402001147
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering. 628 pp. Englisch.
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Buch. Condition: Neu. Data Mining for Scientific and Engineering Applications | R. L. Grossman (u. a.) | Buch | xx | Englisch | 2001 | Springer US | EAN 9781402000331 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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Language: English
Published by Springer US, Springer US Okt 2001, 2001
ISBN 10: 1402000332 ISBN 13: 9781402000331
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications.Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 632 pp. Englisch.
Language: English
Published by Springer US, Humana Okt 2001, 2001
ISBN 10: 1402001142 ISBN 13: 9781402001147
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications.Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 628 pp. Englisch.
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