Big data, data mining and machine learning : value creation for business leaders and practitioners / Jared Dean.
By: Dean, Jared
Series: Wiley & SAS business seriesPublisher: Hoboken, New Jersey : John Wiley and Sons, Inc., c2014Description: xix, 265 pages : illustrations ; 24 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9781118618042 (hardback)Subject(s): Management -- Data processing | Data mining | Big data | Database management | Information technology -- Management | COMPUTERS / Database Management / Data MiningAdditional physical formats: Online version:: High performance data mining and machine learningDDC classification: 658/.05631 LOC classification: HD30.2 | .D39 2014Other classification: COM021030 Summary: "An expert guide to high performance computing architectures and how they relate to analytics and data miningWith the exponential growth of data comes an ever-increasing need to process and analyze so-called Big Data. High Performance Data Mining and Big Data Analytics provides a comprehensive view of the recent trend toward high performance computing architectures and its natural connection to analytics and data mining. You'll find coverage of topics including: big data, high performance computing for analytics, massively parallel processing (MPP) databases, in-memory analytics, implementation of machine learning algorithms for big data platforms, text analytics, analytics environments, the analytics lifecycle, general applications, as well as a variety of cases. Offers coverage of business analytics, predictive modeling, and fact-based management Includes case studies featuring multinational companies Explores recent trends in high performance computing architectures relating to data mining Filled with case studies, High Performance Data Mining and Big Data Analytics provides a thorough grounding for optimally putting data mining and big data analytics to work for your organization"-- Provided by publisher.| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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COLLEGE LIBRARY | COLLEGE LIBRARY SUBJECT REFERENCE | 658.05631 D345 2014 (Browse shelf) | Checked out | 09/18/2025 12:00 AM | CITU-CL-46684 |
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| 658.0558 H143 2000 c.2 Information systems auditing and assurance / | 658.0558 N787 2000 Information systems auditing and assurance / | 658.0558 N787 2000 Information systems auditing and assurance / | 658.05631 D345 2014 Big data, data mining and machine learning : value creation for business leaders and practitioners / | 658.05631 D345 2014 Business information : finding and using data in the digital age / | 658.056312 N388 2014 Commercial data mining : processing, analysis and modeling for predictive analytics projects / | 658.05633 C456 c.2 Applying expert systems in business / |
Includes bibliographical references (pages 247-251) and index.
"An expert guide to high performance computing architectures and how they relate to analytics and data miningWith the exponential growth of data comes an ever-increasing need to process and analyze so-called Big Data. High Performance Data Mining and Big Data Analytics provides a comprehensive view of the recent trend toward high performance computing architectures and its natural connection to analytics and data mining. You'll find coverage of topics including: big data, high performance computing for analytics, massively parallel processing (MPP) databases, in-memory analytics, implementation of machine learning algorithms for big data platforms, text analytics, analytics environments, the analytics lifecycle, general applications, as well as a variety of cases. Offers coverage of business analytics, predictive modeling, and fact-based management Includes case studies featuring multinational companies Explores recent trends in high performance computing architectures relating to data mining Filled with case studies, High Performance Data Mining and Big Data Analytics provides a thorough grounding for optimally putting data mining and big data analytics to work for your organization"-- Provided by publisher.
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