Machine Learning: Theory and Practice

Author:   Jugal Kalita (University of Colorado)
Publisher:   Taylor & Francis Ltd
ISBN:  

9780367433543


Pages:   282
Publication Date:   21 December 2022
Format:   Hardback
Availability:   In Print   Availability explained
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Machine Learning: Theory and Practice


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Full Product Details

Author:   Jugal Kalita (University of Colorado)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   0.535kg
ISBN:  

9780367433543


ISBN 10:   0367433540
Pages:   282
Publication Date:   21 December 2022
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1. Introduction. 2. Regression. 3. Tree-Based Classi cation and Regression. 4. Arti cial Neural Networks. 5. Reinforcement Learning. 6. Unsupervised Learning. 7. Conclusions.

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Author Information

Dr. Jugal Kalita teaches Computer Science at the University of Colorado, Colorado Springs, where he has been a professor since 1990. He received M.S. and Ph.D. degrees in Computer and Information Science from the University of Pennsylvania in Philadelphia in 1988 and 1990, respectively. Prior to that, he had received an M.Sc. in Computational Science from the University of Saskatchewan in Saskatoon, Canada in 1984; and a B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Kharagpur in 1982. Dr. Jugal Kalita’s expertise is in the areas of Artificial Intelligence and Machine Learning, and the application of techniques in Machine Learning to Natural Language Processing, Network Security, and Bioinformatics. At the University of Colorado, Colorado Springs, and Tezpur University, Assam, India, where he is an adjunct professor, Dr. Kalita has supervised 15 Ph.D. and 125 M.S. students to graduation, and has mentored 100 undergraduates in independent research. He has published 250 papers in journals and refereed conferences, including prestigious conferences such as International Conference on Machine Learning (ICML), Association for Advancement of Artificial Intelligence (AAAI), North American Chapter of the Association for Computational Linguistics (NAACL), International Conference on Computational Linguistics (COLING) and Empirical Methods in Natural Language Processing (EMNLP). Dr. Kalita is the author of On Perl: Perl for Students and Professionals, Universal Press, 2003. He is also a co-author of Network Anomaly Detection: A Machine Learning Perspective, CRC Press, 2013; DDOS Attacks: Evolution, Detection, Prevention, Reaction and Tolerance, CRC Press, 2016; Network Traffic Anomaly Detection and Prevention: Concepts, Techniques, and Tools, Springer Nature, 2017; and Gene Expression Data Analysis, A Statistical and Machine Learning Perspective, CRC Press, 2021. Dr. Kalita has received several teaching, research and service awards at the University of Colorado, Colorado Springs, in the Department of Computer Science, and the College of Engineering and Applied Science. He received the prestigious Chancellor's Award at the University of Colorado, Colorado Springs, in 2011, in recognition of lifelong excellence in teaching, research and service. More details about Dr. Kalita can be found at http://www.cs.uccs.edu/~kalita.

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