Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247 ISBN 13: 9783659906244
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247 ISBN 13: 9783659906244
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Aggiungi al carrelloPaperback. Condizione: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247 ISBN 13: 9783659906244
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Knowledge Discovery Using Big Data Analytics | With Practical Approach on Hadoop | Ruchi Agarwal (u. a.) | Taschenbuch | 84 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659906244 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Jun 2016, 2016
ISBN 10: 3659906247 ISBN 13: 9783659906244
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS). 84 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247 ISBN 13: 9783659906244
Da: Majestic Books, Hounslow, Regno Unito
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247 ISBN 13: 9783659906244
Da: Biblios, Frankfurt am main, HESSE, Germania
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247 ISBN 13: 9783659906244
Da: moluna, Greven, Germania
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Agarwal RuchiThe Authors of this book have been actively involved in the research field of Big Data Analytics. They have published various books and papers in international refereed journals and prestigious conferences. Presently, th.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247 ISBN 13: 9783659906244
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS).
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Jun 2016, 2016
ISBN 10: 3659906247 ISBN 13: 9783659906244
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 35,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch.