Verwandte Artikel zu Algorithms in Machine Learning Paradigms: 870 (Studies...

Algorithms in Machine Learning Paradigms: 870 (Studies in Computational Intelligence) - Hardcover

 
9789811510403: Algorithms in Machine Learning Paradigms: 870 (Studies in Computational Intelligence)

Inhaltsangabe

This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning.

 


Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

Dr. Jyotsna Kumar Mandal is a Professor of Computer Science & Engineering, and former Dean of FETM, Kalyani University, India. He holds an M.Sc. in Physics from Jadavpur University, M. Tech. in Computer Science from the University of Calcutta, and was awarded a Ph.D. in Computer Science & Engineering by Jadavpur University. He has 32 years of teaching and research experience in various fields of computer science and allied areas, and has published 170 articles in journals, more than 300 articles at conferences, and edited 31 volumes and seven books. He is a Fellow of IETE, life member of CRSI and CSI, and senior member of IEEE. 

Dr. Somnath Mukhopadhyay is an Assistant Professor at the Department of Computer Science and Engineering, Assam University, Silchar, India. He completed his M.Tech. and Ph.D. degrees in Computer Science and Engineering at the University of Kalyani, India. He has co-authored one book and edited six books and published over 25 papers in various international journals and conference proceedings, including three chapters in edited volumes. His research interests include remote sensing and computational intelligence. He is a life member of the Computer Society of India and currently the Regional Student Coordinator of Region II, Computer Society of India. 

Prof. (Dr.) Paramartha Dutta, FIE (India), FIETE, FOSI, SMIEEE, SMACM, SMCSI, completed his bachelor’s and master’s in Statistics and Master of Technology in Computer Science at the Indian Statistical Institute, and his Ph.D. in Engineering at the Bengal Engineering and Science University, Shibpur. He has co-authored eight books and twelve edited books, and published 250 papers in various peer-reviewed journals and conference proceedings as well as several book chapters. He holds six international and eleven national patents.

Dr. Dutta received (i) IRDP Lifetime Achievement Award 2018, (ii) Distinguished Scientist Award in Computer Science and Engineering 2018 conferred by the Venus International Research Foundation, (iii) Excellence in Science and Technology Award 2018 – 2019 conferred by the Indian Science Congress Association, Government of India, and (iv) INSA Teacher Award 2019 conferred by the Indian National Science Academy, Government of India. 

Dr. Kousik Dasgupta is an Assistant Professor of Computer Science & Engineering, Kalyani Government Engineering College, West Bengal. He completed his B.Tech. in Electronics and Power Engineering at Nagpur University in 1993, M.Tech. in Computer Science at West Bengal University of Technology in 2007, and his Ph.D. at the Department of Computer Science and Engineering, University of Kalyani, in 2017. Dr. Dasgupta has presented numerous papers at various conferences and co-authored several books. He is a member of five scientific and professional societies.

 

Von der hinteren Coverseite

This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning.

 


„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Gratis für den Versand innerhalb von/der Deutschland

Versandziele, Kosten & Dauer

Weitere beliebte Ausgaben desselben Titels

9789811510434: Algorithms in Machine Learning Paradigms: 870 (Studies in Computational Intelligence)

Vorgestellte Ausgabe

ISBN 10:  9811510431 ISBN 13:  9789811510434
Verlag: Springer, 2021
Softcover

Suchergebnisse für Algorithms in Machine Learning Paradigms: 870 (Studies...

Foto des Verkäufers

Jyotsna Kumar Mandal
ISBN 10: 9811510407 ISBN 13: 9789811510403
Neu Hardcover

Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning. Artikel-Nr. 9789811510403

Verkäufer kontaktieren

Neu kaufen

EUR 196,27
Währung umrechnen
Versand: Gratis
Innerhalb Deutschlands
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Verlag: Springer, 2020
ISBN 10: 9811510407 ISBN 13: 9789811510403
Neu Hardcover

Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: New. In. Artikel-Nr. ria9789811510403_new

Verkäufer kontaktieren

Neu kaufen

EUR 190,88
Währung umrechnen
Versand: EUR 5,77
Von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: Mehr als 20 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Mandal, Jyotsna Kumar (Editor) / Mukhopadhyay, Somnath (Editor) / Dutta, Paramartha (Editor) / Dasgupta, Kousik (Editor)
Verlag: Springer, 2020
ISBN 10: 9811510407 ISBN 13: 9789811510403
Neu Hardcover

Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Hardcover. Zustand: Brand New. 208 pages. 9.25x6.10x0.67 inches. In Stock. Artikel-Nr. x-9811510407

Verkäufer kontaktieren

Neu kaufen

EUR 271,52
Währung umrechnen
Versand: EUR 11,58
Von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: 2 verfügbar

In den Warenkorb