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Deep learning techniques and optimization strategies in big data analytics Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series./ [edited by] J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant.
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| dc.contributor.author | Thomas J. Joshua, | |
| dc.date.accessioned | 2024-01-29T21:42:13Z | |
| dc.date.available | 2024-01-29T21:42:13Z | |
| dc.date.issued | 2020 | |
| dc.identifier.citation | Deep learning techniques and optimization strategies in big data analytics Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series. - 1 online resource (xxv, 355 pages). - URL: https://libweb.kpfu.ru/ebsco/pdf/2290014.pdf | |
| dc.identifier.isbn | 1799811948 | |
| dc.identifier.isbn | 9781799811947 | |
| dc.identifier.uri | https://dspace.kpfu.ru/xmlui/handle/net/179792 | |
| dc.description | Includes bibliographical references and index. | |
| dc.description.abstract | "This book examines the application of artificial intelligence in machine learning, data mining in unstructured data sets or databases, web mining, and information retrieval"-- | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.relation.ispartofseries | Advances in Systems Analysis, Software Engineering, and High Performance Computing (ASASEHPC) Book Series | |
| dc.relation.ispartofseries | Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series. | |
| dc.subject.other | Big data. | |
| dc.subject.other | Quantitative research. | |
| dc.subject.other | Big data. | |
| dc.subject.other | Quantitative research. | |
| dc.subject.other | Electronic books. | |
| dc.title | Deep learning techniques and optimization strategies in big data analytics Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series./ [edited by] J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant. | |
| dc.type | Book | |
| dc.description.pages | 1 online resource (xxv, 355 pages). | |
| dc.collection | Электронно-библиотечные системы | |
| dc.source.id | EN05CEBSCO05C45030 |
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