Data mining scientific engineering (31 résultats)
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Data Mining for Scientific and Engineering Applications
Grossman, Robert L. (EDT); Kamath, Chandrika (EDT); Kegelmeyer, Philip (EDT); Kumar, Vipin (EDT); Namburu, Raju R. (EDT)
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Data Mining for Scientific and Engineering Applications (Massive Computing, 2)
Grossman, R.L. [Editor]; Kamath, C. [Editor]; Kegelmeyer, P. [Editor]; Kumar, V. [Editor]; Namburu, R. [Editor];
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paperback. Etat : New. In shrink wrap. Looks like an interesting title.
Data Mining for Scientific and Engineering Applications
Grossman, Robert L. (EDT); Kamath, Chandrika (EDT); Kegelmeyer, Philip (EDT); Kumar, Vipin (EDT); Namburu, Raju R. (EDT)
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Etat : 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.
Data Mining for Scientific and Engineering Applications
Grossman, Robert L. (EDT); Kamath, Chandrika (EDT); Kegelmeyer, Philip (EDT); Kumar, Vipin (EDT); Namburu, Raju R. (EDT)
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Data Mining for Scientific and Engineering Applications
Grossman, Robert L. (EDT); Kamath, Chandrika (EDT); Kegelmeyer, Philip (EDT); Kumar, Vipin (EDT); Namburu, Raju R. (EDT)
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Data Mining for Scientific and Engineering Applications
Grossman, Robert L. (EDT); Kamath, Chandrika (EDT); Kegelmeyer, Philip (EDT); Kumar, Vipin (EDT); Namburu, Raju R. (EDT)
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Data Mining for Scientific and Engineering Applications
Grossman, Robert L. (EDT); Kamath, Chandrika (EDT); Kegelmeyer, Philip (EDT); Kumar, Vipin (EDT); Namburu, Raju R. (EDT)
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Data Mining for Scientific and Engineering Applications
. Ed(s): Grossman, Robert L.; Kamath, Chandrika; Kegelmeyer, P.; Kumar, V.
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Etat : 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 basi…c 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. . . . .
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Etat : New. pp. 628.
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Data Mining for Scientific and Engineering Applications
. Ed(s): Grossman, Robert L.; Kamath, Chandrika; Kegelmeyer, P.; Kumar, V.
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Etat : 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 basi…c 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.
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Taschenbuch. Etat : 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, scienti…sts 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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Buch. Etat : 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.
Data Mining for Scientific and Engineering Applications
Grossman, Robert L. (EDT); Kamath, Chandrika (EDT); Kegelmeyer, Philip (EDT); Kumar, Vipin (EDT); Namburu, Raju R. (EDT)
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Hardcover. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Data Mining for Scientific and Engineering Applications
Grossman, Robert L. (EDT); Kamath, Chandrika (EDT); Kegelmeyer, Philip (EDT); Kumar, Vipin (EDT); Namburu, Raju R. (EDT)
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Data Mining for Scientific and Engineering Applications
Grossman, R. L.|Kamath, C.|Kegelmeyer, P.|Kumar, V.|Namburu, R.
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Gebunden. Etat : 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 usefu…l information in these data sets, scientist.
Data Mining for Scientific and Engineering Applications
Grossman, R. L.|Kamath, C.|Kegelmeyer, P.|Kumar, V.|Namburu, R.
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Etat : 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 informat…ion in these data sets, scientist.
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Taschenbuch. Etat : 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 da…ta 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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Taschenbuch. Etat : 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 s…ets, 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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Buch. Etat : 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, sc…ientists 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.
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Buch. Etat : 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. 632 pp. Englisch.
