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Machine learning applications : emerging trends /
The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges t...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin ; Boston :
Walter de Gruyter GmbH,
[2020]
|
| Colección: | De Gruyter frontiers in computational intelligence ;
5. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 001 | KNOVEL_on1153563321 | ||
| 003 | OCoLC | ||
| 005 | 20231027140348.0 | ||
| 006 | m o d | ||
| 007 | cr ||||||||||| | ||
| 008 | 200424s2020 gw fob z001 0 eng d | ||
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| 019 | |a 1151189531 | ||
| 020 | |a 9783110610987 |q (electronic book) | ||
| 020 | |a 3110610981 |q (electronic book) | ||
| 020 | |a 3110608669 |q (electronic book) | ||
| 020 | |a 9783110608663 |q (electronic bk.) | ||
| 020 | |z 9783110608533 | ||
| 020 | |z 3110608537 | ||
| 024 | 7 | |a 10.1515/9783110610987 |2 doi | |
| 029 | 1 | |a AU@ |b 000068359589 | |
| 035 | |a (OCoLC)1153563321 |z (OCoLC)1151189531 | ||
| 050 | 4 | |a Q325.5 |b .M33 2020 | |
| 072 | 7 | |a COM004000 |2 bisacsh | |
| 082 | 0 | 4 | |a 006.3/1 |2 23 |
| 049 | |a UAMI | ||
| 245 | 0 | 0 | |a Machine learning applications : |b emerging trends / |c edited by Rik Das, Siddhartha Bhattacharyya, Sudarshan Nandy. |
| 264 | 1 | |a Berlin ; |a Boston : |b Walter de Gruyter GmbH, |c [2020] | |
| 300 | |a 1 online resource (x, 135 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file | ||
| 347 | |b PDF | ||
| 490 | 1 | |a De Gruyter frontiers in computational intelligence ; |v volume 5 | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | 0 | |t Frontmatter -- |t Dedication -- |t Preface -- |t Inhalt -- |t 1 A prologue to Emerging trends in Machine Learning -- |t 2 An Analysis on Non-linear Dimension Reduction Techniques -- |t 3 Application of Machine Learning in Music Analytics -- |t 4 A Comparative Analysis of Machine Learning Techniques for Odia Character Recognition -- |t 5 Pre Filtering with Rule Mining for Context Based Recommendation System -- |t 6 Early detection of crop diseases using machine Learning based intelligent techniques: a review -- |t 7 Conclusion -- |t Contributing authors -- |t Index |
| 520 | |a The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice. | ||
| 546 | |a In English. | ||
| 588 | 0 | |a Online resource; title from digital title page (viewed on September 15, 2020). | |
| 590 | |a Knovel |b ACADEMIC - Software Engineering | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 7 | |a COMPUTERS |x Intelligence (AI) & Semantics. |2 bisacsh | |
| 650 | 7 | |a Machine learning |2 fast | |
| 700 | 1 | |a Das, Rik, |d 1978- |e editor. | |
| 700 | 1 | |a Bhattacharyya, Siddhartha, |e editor. | |
| 700 | 1 | |a Nandy, Sudarshan, |e editor. | |
| 776 | 0 | 8 | |i Print version: |z 9783110608663 |
| 776 | 0 | 8 | |i Print version: |z 9783110608533 |
| 830 | 0 | |a De Gruyter frontiers in computational intelligence ; |v 5. | |
| 856 | 4 | 0 | |u https://appknovel.uam.elogim.com/kn/resources/kpMLAET004/toc |z Texto completo |
| 938 | |a De Gruyter |b DEGR |n 9783110610987 | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL6269886 | ||
| 938 | |a EBSCOhost |b EBSC |n 2435800 | ||
| 938 | |a YBP Library Services |b YANK |n 301223752 | ||
| 938 | |a YBP Library Services |b YANK |n 16346210 | ||
| 994 | |a 92 |b IZTAP | ||