{"product_id":"machine-learning-theory-and-practice-paperback","title":"Machine Learning: Theory and Practice - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eJugal Kalita\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMachine Learning: Theory and Practice\u003c\/em\u003e\u003c\/strong\u003e provides an introduction to the most popular methods in machine learning. The book covers regression including regularization, tree-based methods including Random Forests and Boosted Trees, Artificial Neural Networks including Convolutional Neural Networks (CNNs), reinforcement learning, and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid, illustrated with figures and examples. For each machine learning method discussed, the book presents appropriate libraries in the R programming language along with programming examples. \u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eFeatures: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eProvides an easy-to-read presentation of commonly used machine learning algorithms in a manner suitable for advanced undergraduate or beginning graduate students, and mathematically and\/or programming-oriented individuals who want to learn machine learning on their own.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eCovers mathematical details of the machine learning algorithms discussed to ensure firm understanding, enabling further exploration\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003ePresents worked out suitable programming examples, thus ensuring conceptual, theoretical and practical understanding of the machine learning methods.\u003c\/li\u003e \u003c\/ul\u003e\u003cp\u003eThis book is aimed primarily at introducing essential topics in Machine Learning to advanced undergraduates and beginning graduate students. The number of topics has been kept deliberately small so that it can all be covered in a semester or a quarter. The topics are covered in depth, within limits of what can be taught in a short period of time. Thus, the book can provide foundations that will empower a student to read advanced books and research papers.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eDr. Jugal Kalita\u003c\/strong\u003e 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. \u003c\/p\u003e\u003cp\u003eDr. 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 \u003ci\u003eInternational Conference on Machine Learning\u003c\/i\u003e (ICML), \u003ci\u003eAssociation for Advancement of Artificial Intelligence\u003c\/i\u003e (AAAI), \u003ci\u003eNorth American Chapter of the Association for Computational Linguistics \u003c\/i\u003e(NAACL), \u003ci\u003eInternational Conference on Computational Linguistics\u003c\/i\u003e (COLING) and \u003ci\u003eEmpirical Methods in Natural Language Processing\u003c\/i\u003e (EMNLP). Dr. Kalita is the author of \u003ci\u003eOn Perl: Perl for Students and Professionals\u003c\/i\u003e, Universal Press, 2003. He is also a co-author of \u003ci\u003eNetwork Anomaly Detection: A Machine Learning Perspective\u003c\/i\u003e, CRC Press, 2013; \u003ci\u003eDDOS Attacks: Evolution, Detection, Prevention, Reaction and Tolerance\u003c\/i\u003e, CRC Press, 2016; \u003ci\u003eNetwork Traffic Anomaly Detection and Prevention: Concepts, Techniques, and Tools\u003c\/i\u003e, Springer Nature, 2017; and \u003ci\u003eGene Expression Data Analysis, A Statistical and Machine Learning Perspective\u003c\/i\u003e, CRC Press, 2021. \u003c\/p\u003e\u003cp\u003eDr. 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.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 282\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.63 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e December 19, 2024\u003c\/div\u003e\n            ","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":53577437741363,"sku":"9780367433529","price":103.66,"currency_code":"USD","in_stock":true}],"url":"https:\/\/s3xxpj-vy.myshopify.com\/products\/machine-learning-theory-and-practice-paperback","provider":"The Celestial Starlit Phoenix ","version":"1.0","type":"link"}