Data Science and SDGs: Challenges, Opportunities and Realities - Tapa dura

 
9789811619182: Data Science and SDGs: Challenges, Opportunities and Realities
Tapa dura
ISBN 10: 9811619182 ISBN 13: 9789811619182
Editorial: Springer, 2021

Sinopsis

The book presents contributions on statistical models and methods applied, for both data science and SDGs, in one place. Measuring and controlling data of SDGs, data driven measurement of progress needs to be distributed to stakeholders. In this situation, the techniques used in data science, specially, in the big data analytics, play an important role rather than the traditional data gathering and manipulation techniques. This book fills this space through its twenty contributions. The contributions have been selected from those presented during the 7th International Conference on Data Science and Sustainable Development Goals organized by the Department of Statistics, University of Rajshahi, Bangladesh; and cover topics mainly on SDGs, bioinformatics, public health, medical informatics, environmental statistics, data science and machine learning.

The contents of the volume would be useful to policymakers, researchers, government entities, civil society, and nonprofit organizations for monitoring and accelerating the progress of SDGs.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Professor Bikas K Sinha has been publishing Springer monographs and edited volumes since 1989. Besides being an academic with Indian Statistical Institute [1979-2011], he has served Government of India as a Member of National Statistical Commission for the 3-year period 2006-2009. His research publications span both statistical theory and applications. He was appointed an ‘Expert on Mission’ for the United Nations-funded Workshop on Survey Methodology in 1991. Professor Sinha has travelled extensively worldwide with teaching/research/consultancy assignments. He has held various academic assignments in international institutes.

Professor Nurul Haque Mollah is attached to the Department of Statistics, University of Rajshahi, Bangladesh. He completed his PhD degree research (2002-2005) in Statistical Science from the Institute of Statistical Mathematics (ISM), Tokyo, Japan. He also completed his post-doctoral research (2006-2008) in bioinformatics from ISM, Tokyo, Japan.  His area of research specialization covers multivariate statistics, robust statistical inference, statistical signal processing, data mining, bioinformatics and computational biology. He has published 170 research articles, book chapters in refereed journals, books and proceedings of international conferences so far. He has supervised more than 50 research students at Master and PhD levels. He successfully led, as the Principal Investigator (PI), several research projects funded by UGC, NST, BANBEIS and World Bank. He also organized several national/international workshops, seminars and conferences as convener/co-convener. He is the convener of BioRGSD (Bioinformatics Research Group of Statistics Department, RU) & BioRGRU (Bioinformatics Research Group, RU). He is also the Founder President of BBCBA (Bangladesh Bioinformatics and Computational Biology Association).

 

De la contraportada

The book presents contributions on statistical models and methods applied, for both data science and SDGs, in one place. Measuring and controlling data of SDGs, data driven measurement of progress needs to be distributed to stakeholders. In this situation, the techniques used in data science, specially, in the big data analytics, play an important role rather than the traditional data gathering and manipulation techniques. This book fills this space through its twenty contributions. The contributions have been selected from those presented during the 7th International Conference on Data Science and Sustainable Development Goals organized by the Department of Statistics, University of Rajshahi, Bangladesh; and cover topics mainly on SDGs, bioinformatics, public health, medical informatics, environmental statistics, data science and machine learning.

The contents of the volume would be useful to policymakers, researchers, government entities, civil society, and nonprofit organizations for monitoring and accelerating the progress of SDGs.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2021
Idioma
Inglés
ISBN 10 
9811619182
ISBN 13 
9789811619182
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
220
Editor
Sinha Bikas Kumar, Mollah Md. Nurul Haque
Contacto del fabricante
Springer Nature Customer Service Center GmbH
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9789811619212: Data Science and SDGs: Challenges, Opportunities and Realities

Edición Destacada

ISBN 10:  9811619212 ISBN 13:  9789811619212
Editorial: Springer, 2022
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