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Synopsis
The well-known Machine Learning systems generally use a power and resources of only one personal computer. Nowadays, new devices, social media, and other sources generate the data of huge volumes. More innovative technologies which would be need for big data analysis. The selection of the strategy depends on the volume of data analysed. When we deal with a large data set, the well-known data mining systems usually are used. The complex problems of data analysis require usage of parallel and distributed computing based systems and technologies. Big data initiate development of new technologies. Hadoop based technologies and libraries are the most popular solutions for big data analysis and clustering. Machine learning is ideal for exploiting the opportunities hidden in big data. It delivers on the promise of extracting value from big and disparate data sources with far less reliance on human direction. It is data driven and runs at machine scale. It is well suited to the complexity of dealing with disparate data sources and the huge variety of variables and amounts of data involved. And unlike traditional analysis, machine learning thrives on growing data sets.
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About the Author
Gudikandhula Narasimha Rao received M.Tech in CSE from A.N.University, Guntur. He currently pursues PhD in Deptartment of Geo-Engg, Andhra University, Visakhapatnam. He published several research papers in National and International referred Journals. His areas of interests are Disaster Management, Spatial Semantics and Machine Learning.
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Machine Learning for Text Classification in Big Data Analytics
Published by
LAP LAMBERT Academic Publishing Nov 2016, 2016
ISBN 10: 3659946877
ISBN 13: 9783659946875
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The well-known Machine Learning systems generally use a power and resources of only one personal computer. Nowadays, new devices, social media, and other sources generate the data of huge volumes. More innovative technologies which would be need for big data analysis. The selection of the strategy depends on the volume of data analysed. When we deal with a large data set, the well-known data mining systems usually are used. The complex problems of data analysis require usage of parallel and distributed computing based systems and technologies. Big data initiate development of new technologies. Hadoop based technologies and libraries are the most popular solutions for big data analysis and clustering. Machine learning is ideal for exploiting the opportunities hidden in big data. It delivers on the promise of extracting value from big and disparate data sources with far less reliance on human direction. It is data driven and runs at machine scale. It is well suited to the complexity of dealing with disparate data sources and the huge variety of variables and amounts of data involved. And unlike traditional analysis, machine learning thrives on growing data sets. 96 pp. Englisch. Seller Inventory # 9783659946875
Quantity: 2 available
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Machine Learning for Text Classification in Big Data Analytics
Published by
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659946877
ISBN 13: 9783659946875
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The well-known Machine Learning systems generally use a power and resources of only one personal computer. Nowadays, new devices, social media, and other sources generate the data of huge volumes. More innovative technologies which would be need for big data analysis. The selection of the strategy depends on the volume of data analysed. When we deal with a large data set, the well-known data mining systems usually are used. The complex problems of data analysis require usage of parallel and distributed computing based systems and technologies. Big data initiate development of new technologies. Hadoop based technologies and libraries are the most popular solutions for big data analysis and clustering. Machine learning is ideal for exploiting the opportunities hidden in big data. It delivers on the promise of extracting value from big and disparate data sources with far less reliance on human direction. It is data driven and runs at machine scale. It is well suited to the complexity of dealing with disparate data sources and the huge variety of variables and amounts of data involved. And unlike traditional analysis, machine learning thrives on growing data sets. Seller Inventory # 9783659946875
Quantity: 1 available
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Machine Learning for Text Classification in Big Data Analytics
Published by
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659946877
ISBN 13: 9783659946875
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Paperback. Condition: Brand New. 96 pages. 8.66x5.91x0.22 inches. In Stock. Seller Inventory # 3659946877
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Machine Learning for Text Classification in Big Data Analytics
Published by
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659946877
ISBN 13: 9783659946875
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gudikandhula Narasimha RaoGudikandhula Narasimha Rao received M.Tech in CSE from A.N.University, Guntur. He currently pursues PhD in Deptartment of Geo-Engg, Andhra University, Visakhapatnam. He published several research papers in N. Seller Inventory # 158249162
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Machine Learning for Text Classification in Big Data Analytics
Published by
LAP LAMBERT Academic Publishing Nov 2016, 2016
ISBN 10: 3659946877
ISBN 13: 9783659946875
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. Neuware -The well-known Machine Learning systems generally use a power and resources of only one personal computer. Nowadays, new devices, social media, and other sources generate the data of huge volumes. More innovative technologies which would be need for big data analysis. The selection of the strategy depends on the volume of data analysed. When we deal with a large data set, the well-known data mining systems usually are used. The complex problems of data analysis require usage of parallel and distributed computing based systems and technologies. Big data initiate development of new technologies. Hadoop based technologies and libraries are the most popular solutions for big data analysis and clustering. Machine learning is ideal for exploiting the opportunities hidden in big data. It delivers on the promise of extracting value from big and disparate data sources with far less reliance on human direction. It is data driven and runs at machine scale. It is well suited to the complexity of dealing with disparate data sources and the huge variety of variables and amounts of data involved. And unlike traditional analysis, machine learning thrives on growing data sets.Books on Demand GmbH, Überseering 33, 22297 Hamburg 96 pp. Englisch. Seller Inventory # 9783659946875
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