Machine Learning for Network Management (Textbooks in Telecommunication Engineering) （2026. Approx. 200 p. 50 illus. in color. 279 mm）

Caicedo Rendon, Oscar

SPRINGER, BERLIN; SPRINGER（2026/05発売）

• 製本 Hardcover:ハードカバー版
• 商品コード 9783032151759

Full Description

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.

 

Contents

Introduction.- Part I.- Network Management.- Machine Learning.- Part II.- Network Management Assisted by Supervised and Semi-supervised Learning.- Network Management Driven by Unsupervised Learning.- Network Management Assisted by Reinforcement Learning.- Part III.- ML-Driven Management of Softwarized Networks.- ML-Driven Management of Next Generation Networks.- Conclusion.