Sprache: Englisch
Verlag: Cambridge University Press, 2020
ISBN 10: 1108476341 ISBN 13: 9781108476348
Anbieter: WorldofBooks, Goring-By-Sea, WS, Vereinigtes Königreich
EUR 31,49
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In den WarenkorbPaperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Sprache: Englisch
Verlag: Cambridge University Press, 2020
ISBN 10: 1108476341 ISBN 13: 9781108476348
Anbieter: Books From California, Simi Valley, CA, USA
hardcover. Zustand: Very Good.
Sprache: Englisch
Verlag: Cambridge University Press, 2020
ISBN 10: 1108476341 ISBN 13: 9781108476348
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 91,02
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Cambridge University Press, 2020
ISBN 10: 1108476341 ISBN 13: 9781108476348
Anbieter: Kennys Bookstore, Olney, MD, USA
EUR 121,53
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In den WarenkorbZustand: New. 2020. 3rd Edition. Hardcover. . . . . . Books ship from the US and Ireland.
EUR 131,86
Anzahl: 2 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 3rd edition. 553 pages. 9.75x7.00x1.00 inches. In Stock.
Sprache: Englisch
Verlag: Cambridge University Press, 2020
ISBN 10: 1108476341 ISBN 13: 9781108476348
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.