Вышел учебник по применению машинного обучения в управлении телекоммуникационными сетями

Overview Authors: Oscar Mauricio Caicedo Rendon   ORCID: https://orcid.org/0000-0003-2223-947X 0 Oscar Mauricio Caicedo Rendon University of Cauca, Popayán, Colombia Search author on: PubMed Google Scholar Presents network management challenges approached through the use of machine learning and reviews their solutions Describes the machine learning applications to network management for real world use Includes a full suite of classroom materials including exercises, Q&A, and examples Part of the book series: Textbooks in Telecommunication Engineering (TTE) 83 Accesses This is a preview of subscription content, to check access. Access this book eBook USD 89.00 Price excludes VAT (USA) Hardcover Book USD 119.99 Price excludes VAT (USA) Tax calculation will be finalised at checkout Other ways to access About this book This book details how machine learning (ML) can be used in network management. Geared towards an upper undergraduate or graduate level class in machine learning or computer networks, the author showcases the intersection between ML/artificial intelligence (AI) and network management paradigms. The book includes practical methodologies and guidelines to realizing AI/ML-driven network management. The book also provides a landscape of AI/ML techniques more relevant to network management while also presenting AI/ML-based network management solutions deployed in production environments so students can explore applications. The book features homework problems, exercises, case studies, and PowerPoint slides. Table of contents (8 chapters) Front Matter Pages i-xix Preliminaries Front Matter Pages 1-1 Introduction Oscar Mauricio Caicedo Rendón Pages 3-9 Network Management: A Primer Oscar Mauricio Caicedo Rendón Pages 11-32 Machine Learning in Networking: An  Overview Oscar Mauricio Caicedo Rendón Pages 33-46 Network Management Driven by Learning Models Front Matter Pages 47-47 Network Management Assisted by  Supervised Learning Oscar Mauricio Caicedo Rendón Pages 49-80 Network Management Driven by  Unsupervised Learning Oscar Mauricio Caicedo Rendón Pages 81-101 Deep Reinforcement Learning  for  Network  Management Oscar Mauricio Caicedo Rendón Pages 103-130 Network Management  Assisted by Generative Learning Oscar Mauricio Caicedo Rendón Pages 131-155 Exemplifying Machine Learning in Network Management Front Matter Pages 157-157 Improving and Explaining Learning Models Oscar Mauricio Caicedo Rendón Pages 159-177 Back Matter Pages 179-180 Authors and Affiliations University of Cauca, Popayán, Colombia Oscar Mauricio Caicedo Rendon About the author Oscar Mauricio Caicedo Rendón is a full professor at the Universidad del Cauca (Unicauca), Colombia, where he is a member of the Telematics Engineering Group of the Faculty of Telecommunications Engineering. He received his Ph.D. in Computer Science from the Federal University of Rio Grande do Sul, Brazil (2015), and his M.Sc. in Telematics Engineering (2006) as well as his degree in Electronics and Telecommunications Engineering (2001) from Unicauca. He is an IEEE Senior Member (since 2020) and has been classified as a Senior Researcher by MinCiencias Colombia since 2018. He has also served as a visiting professor at the University of Campinas (Unicamp), Brazil, in 2018 and 2022. Prof. Caicedo Rendón is Series Editor for the IEEE Communications Magazine Series on Network Softwarization and Management, and an Associate Editor for IEEE Networking Letters, the IEEE Internet of Things Journal, and the IEEE Latin American Transactions. He served as General Chair of the IEEE Colombian Conference on Communications and Computing and Technical Program Co-Chair for IEEE LATINCOM 2020 and for the Machine Learning for Communications and Networking Symposium at IEEE GLOBECOM 2022. He continues to participate as a TPC member in various IEEE-sponsored international conferences and workshops, including NetSoft, CNMS, NOMS, EuCNC, and CloudNet, as well as reviewer in important venues like IEEE Transactions on Network and Service Management, IEEE Transactions on Network Science and Engineering, and IEEE Transactions on Cognitive Communications and Networking, His current research interests include network and service management, network functions virtualization, software-defined networking, machine learning for networking, and network softwarization. Accessibility Information This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility. It includes screen reader support, descriptions for Non-text content (such as images and graphs), bookmarks for easy navigation, keyboard-friendly links and forms, and searchable, selectable text. We recognise the importance of accessibility and welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us via https://www.springernature.com/gp/info/accessibility Please Note that a more accessible version of this eBook is available as an EPUB. EPUB accessibility summary This EPUB is designed with accessibility in mind, aiming to meet the EPUB Accessibility 1.1 and WCAG 2.2 Level AA standards. It features a navigable table of contents, structured headings, and alternative text for images, ensuring smooth, intuitive navigation and comprehension. The text is reflowable and resizable, with sufficient contrast. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us via https://www.springernature.com/gp/info/accessibility Bibliographic Information Book Title: Machine Learning for Network Management Authors: Oscar Mauricio Caicedo Rendon Series Title: Textbooks in Telecommunication Engineering DOI: https://doi.org/10.1007/978-3-032-15176-6 Publisher: Springer Cham eBook Packages: Engineering, Engineering (R0) Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2026 Hardcover ISBN: 978-3-032-15175-9 Published: 09 September 2026 Softcover ISBN: 978-3-032-15178-0 Due: 23 September 2027 eBook ISBN: 978-3-032-15176-6 Published: 07 September 2026 Series ISSN: 2524-4345 Series E-ISSN: 2524-4353 Edition Number: 1 Number of Pages: XIX, 179 Number of Illustrations: 1 b/w illustrations, 35 illustrations in colour Topics: Communications Engineering, Networks, Computer Communication Networks, Machine Learning Keywords Network management Zero touch network & service management Autonomous network management Supervised, Semi-supervised, and Unsupervised Learning Reinforcement Learning Publish with us