Handbook of research on big data clustering and machine learning / [edited by] Fausto Pedro Garcia Marquez.
"As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly....
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| Other Authors: | |
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| Format: | Ebook |
| Language: | English |
| Published: |
Hershey, PA :
Engineering Science Reference (an imprint of IGI Global),
[2020]
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| Series: | Advances in data mining and database management (ADMDM) book series.
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| Subjects: | |
| Online Access: | IGI Global e-Book Collection |
| Summary: | "As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is necessary. The Handbook of Research on Big Data Clustering and Machine Learning is an essential reference source that synthesizes the analytic principles of clustering and machine learning to big data and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management. Featuring research on topics such as project management, contextual data modeling, and business information systems, this book is ideally designed for engineers, economists, finance officers, marketers, decision makers, business professionals, industry practitioners, academicians, students, and researchers seeking coverage on the implementation of big data and machine learning within specific professional fields."--Publisher's website. |
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| Physical Description: | 1 online resource (xxi, 478 pages). |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 1799801063 9781799801061 |