kegelmeyer (17 Ergebnisse)

Hardcover. Zustand: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

hardcover. Zustand: Good. Our good condition books are generally good for reading but not for gifting or collecting. They could have imperfections such as creasing, fanning, inscriptions, margin notes, yellowing, staining on edge or cover or pages, bumps, scuffs, etc etc (sometimes multiple of these). It's a wide category that encompasses anything that isn't almost-new down to anything that is slightly better than poor. We would NOT recommend gifting Good books - these should be considered reading copies. Our books are dispatched from a Yorkshire former cotton mill. We list via barcode/ISBN so please note that the images are stock images and may not be the exact copy you receive, furthermore the details about edition and year might not be accurate as many publishers reuse the same ISBN for multiple editions and as we simply scan a barcode or enter an ISBN we do not check the validity of the edition data when listing. If you're looking for an exact edition please don't order (at least not without checking with us first, although we don't always have time to check). We aim to dispatch prompty, the service used will depend on order value and book size. We can ship to most countries, see our shipping policies. Payment is via Abe only.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New.

Zustand: New. In.

Zustand: NEW.

Zustand: 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.

Hardcover. Zustand: Brand New. 2nd edition. 704 pages. 10.75x8.75x1.50 inches. In Stock.

Zustand: New. 2024. 2nd Edition. hardcover. . . . . . Books ship from the US and Ireland.

Zustand: New. &Uumlber den AutorDeborah Larsen, PT, PhD, (retired) is the former director of the School of Health and Rehabilitation Sciences former associate dean of the College of Medicine former associate vice president for Health.

Zustand: New. A full-color neuroscience text that skillfully integrates neuromuscular skeletal content&Uumlber den AutorDeborah Larsen, PT, PhD Director, School of Health and Rehabilitation Sciences Associate Dean, College of Medicine.

Zustand: New. In.

Zustand: New. In.

Taschenbuch. Zustand: 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.

Zustand: 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. Zustand: 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.

Buch. Zustand: 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.