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Record Nr. |
UNINA9910554227403321 |
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Titolo |
Machine learning for sustainable development / / edited by Kamal Kant Hiran [and three others] |
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Pubbl/distr/stampa |
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Berlin ; ; Boston : , : De Gruyter, , [2021] |
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©2021 |
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ISBN |
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1-5231-5446-2 |
3-11-070251-7 |
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Descrizione fisica |
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1 online resource (XIII, 201 p.) |
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Collana |
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De Gruyter Frontiers in Computational Intelligence ; ; 9 |
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Classificazione |
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Disciplina |
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Soggetti |
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Sustainable development |
Machine learning |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Frontmatter -- Preface -- Contents -- About editors -- List of contributors -- Chapter 1. A framework for applying artificial intelligence (AI) with Internet of nanothings (IoNT) -- Chapter 2 Opportunities and challenges in transforming higher education through machine learning -- Chapter 3 Efficient renewable energy integration: a pertinent problem and advanced time series data analytics solution -- Chapter 4 A comprehensive review on the application of machine learning techniques for analyzing the smart meter data -- Chapter 5 Application of machine learning algorithms for facial expression analysis -- Chapter 6 Prediction of quality analysis for crop based on machine learning model -- Chapter 7 Data model recommendations for real-time machine learning applications: a suggestive approach -- Chapter 8 Machine learning for sustainable agriculture -- Chapter 9 Application of machine learning in SLAM algorithms -- Chapter 10 Machine learning for weather forecasting -- Chapter 11 Applications of conventional machine learning and deep learning for automation of diagnosis: case study -- Index |
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Sommario/riassunto |
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The book will focus on the applications of machine learning for sustainable development. Machine learning (ML) is an emerging technique whose diffusion and adoption in various sectors (such as |
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