Overview
- Discusses the applications of machine learning in artificial intelligence
- A valuable resource for researchers in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics
- Covers human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences
Part of the book series: Algorithms for Intelligent Systems (AIS)
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Table of contents (24 chapters)
Keywords
About this book
Editors and Affiliations
About the editors
Dr. Jitendra Kumar Verma is Assistant Professor (Grade III) of Computer Science & Engineering at Amity School of Engineering & Technology, Amity University Haryana, Gurugram (Manesar), India. He received the degree of Ph.D. from Jawaharlal Nehru University (JNU), New Delhi, India in 2017, degree of M.Tech from JNU in 2013 and degree of B.Tech in Computer Science & Engineering from Kamla Nehru Institute of Technology (KNIT), Sultanpur, Uttar Pradesh, India in 2008. Dr. Verma is awardee of prestigious DAAD "A new Passage to India" Fellowship (2015-16) funded by Federal Ministry of Education and Research - BMBF, Germany and German Academic Exchange Service (DAAD). He worked at JULIUS-MAXIMILIAN UNIVERSITY OF WÃœRZBURG, GERMANY (mother of 14 Nobel Laureate) as a Visiting Research Scholar. Dr. Verma is member of several technical societies e.g. IEEE, IEEE IAS, and ACM. Over his short career, he published several research papers in proceedings of various international conferences and peer-reviewed International Journals of repute. He also contributed numerous book chapters to the several books published with publishers of high international repute. Apart from scholarly contribution towards scientific community, he organized several Conferences/Workshops/Seminars at the national and international levels. He voluntarily served as reviewer for various International Journals, conferences, and workshops. He also served as Guest Editor and Editorial Board Member of numerous international journals. His research interest includes cloud computing, Mobile cloud, Machine learning, AR & VR, Soft computing, Fuzzy systems, Healthcare, Pattern recognition, Bio-inspired phenomena, and advanced optimization model & computation.
Dr. Sudip Paul is an Assistant Professor at the Department of Biomedical Engineering, School of Technology, North-Eastern Hill University (NEHU), Shillong, India. He received his Ph.D. from the Indian Institute of Technology (Banaras Hindu University), Varanasi, with a specialization in Electrophysiology and Brain Signal Analysis. He was selected as a Postdoc Fellow in 2017–18 under the Biotechnology Overseas Associateship for scientists working in the Northeastern States of India, supported by the Department of Biotechnology, Government of India. Dr. Sudip has published morethan 90 international journal and conference papers and has filed four patents. Recently, he completed three book projects and is currently serving as Editor for a further two. Dr. Sudip is a member of numerous societies and professional bodies, e.g. the APSN, ISN, IBRO, SNCI, SfN, and IEEE. He received First Prize in the Sushruta Innovation Award 2011, sponsored by the Department of Science and Technology, Government of India, and various other awards, including a World Federation of Neurology (WFN) Travelling Fellowship, Young Investigator Award, and IBRO and ISN Travel Awards. Dr. Sudip has also served as an editorial board member for a variety of international journals.
Bibliographic Information
Book Title: Applications of Machine Learning
Editors: Prashant Johri, Jitendra Kumar Verma, Sudip Paul
Series Title: Algorithms for Intelligent Systems
DOI: https://doi.org/10.1007/978-981-15-3357-0
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2020
Hardcover ISBN: 978-981-15-3356-3Published: 05 May 2020
Softcover ISBN: 978-981-15-3359-4Published: 05 May 2021
eBook ISBN: 978-981-15-3357-0Published: 04 May 2020
Series ISSN: 2524-7565
Series E-ISSN: 2524-7573
Edition Number: 1
Number of Pages: XXII, 394
Number of Illustrations: 46 b/w illustrations, 112 illustrations in colour
Topics: Mathematical and Computational Engineering, Signal, Image and Speech Processing, Machine Learning, Image Processing and Computer Vision, Logic in AI, Probability and Statistics in Computer Science