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Machine Learning for Sustainable Development / ed. by Kamal Kant Hiran, Deepak Khazanchi, Ajay Kumar Vyas, Sanjeevikumar Padmanaban.

Contributor(s): Alsharif, Futoon [contributor.] | Aluvalu, Rajanikanth [contributor.] | Bandhu, Kailash Chandra [contributor.] | Bashawyah, Doaa A [contributor.] | Bhansali, Ashok [contributor.] | Chhabra Gandhi, Geeta [contributor.] | Dadhich, Manish [contributor.] | Dadhich, Shruti [contributor.] | Doshi, Ruchi [contributor.] | Guha, Radha [contributor.] | Guruvare, Shyamala [contributor.] | Hegde, Roopa B [contributor.] | Jain, Vipin [contributor.] | Jayaprakash, Sujith [contributor.] | Kalla, Mukesh [contributor.] | Kant Hiran, Kamal [editor.] | Kathiresan, V [contributor.] | Keerthi Chennam, Krishna [contributor.] | Khazanchi, Deepak [contributor.] | Khazanchi, Deepak [editor.] | Kudva, Vidya [contributor.] | Kumar Vyas, Ajay [editor.] | Lakhwani, Kamlesh [contributor.] | Maheswari, Uma V [contributor.] | Mahrishi, Mehul [contributor.] | Mathew, Ammu Anna [contributor.] | Mishra, Anoop [contributor.] | Mithal, Amit [contributor.] | Mittal, Rohit [contributor.] | Morwal, Sudha [contributor.] | Padmanaban, Sanjeevikumar [editor.] | Pathak, Vibhakar [contributor.] | Prasad, Keerthana [contributor.] | Qaisar, Saeed Mian [contributor.] | Saxena, Swati [contributor.] | Shanmugapriya, N [contributor.] | Sharma, Girish [contributor.] | Singh, Brij Mohan [contributor.] | Subasi, Abdulhamit [contributor.] | Tripathi, Abhishek [contributor.] | Vivekanandan, S [contributor.].
Material type: materialTypeLabelBookSeries: De Gruyter Frontiers in Computational Intelligence , 9.Publisher: Berlin ; Boston : De Gruyter, [2021]Copyright date: ©2021Description: 1 online resource (XIII, 201 p.).Content type: text Media type: computer Carrier type: online resourceISBN: 9783110702514.Subject(s): Internet der Dinge | Künstliche Intelligenz | Maschinelles Lernen | Nachhaltige Entwicklung | Artificial Intelligence | Machine Learning | Sustainable DevelopmentAdditional physical formats: No title; No titleOther classification: ST 300 Online resources: Click here to access online | Click here to access online | Cover Issued also in print.
Contents:
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
Title is part of eBook package:DG Ebook Package English 2021Title is part of eBook package:DG Plus DeG Package 2021 Part 1Title is part of eBook package:EBOOK PACKAGE COMPLETE 2021 EnglishTitle is part of eBook package:EBOOK PACKAGE COMPLETE 2021Title is part of eBook package:EBOOK PACKAGE Engineering, Computer Sciences 2021 EnglishTitle is part of eBook package:EBOOK PACKAGE Engineering, Computer Sciences 2021Summary: 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 energy, agriculture, internet of things, infrastructure) will be of enormous benefit. The state of the art of machine learning models is most useful for forecasting and prediction of various sectors for sustainable development.
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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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http://purl.org/coar/access_right/c_16ec

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 energy, agriculture, internet of things, infrastructure) will be of enormous benefit. The state of the art of machine learning models is most useful for forecasting and prediction of various sectors for sustainable development.

Issued also in print.

Mode of access: Internet via World Wide Web.

In English.

Description based on online resource; title from PDF title page (publisher's Web site, viewed 28. Feb 2023)

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