Book
Principles of Machine Learning
ISBN : 9789819753321
Author : Wenmin Wang
Publisher : Springer
Year : 2025
Language : English
Type : Book
Description : The book is structured into four parts, encompassing a total of fifteen chapters. The inaugural part, titled “Perspectives,” comprises two chapters: an introductory exposition and an exploration of the conceptual foundations. The second part, “Frameworks”: subdivided into five chapters, each dedicated to the discussion of five seminal frameworks: probability, statistics, connectionism, symbolism, and behaviorism. Continuing further, the third part, “Paradigms,” encompasses four chapters that explain the three paradigms of supervised learning, unsupervised learning, and reinforcement learning, and narrating several quasi-paradigms emerged in machine learning. Finally, the fourth part, “Tasks”: comprises four chapters, delving into the prevalent learning tasks of classification, regression, clustering, and dimensionality reduction.
RECOMMENDED BOOKS
Non Additive Geometry
Shai Haran
China in India's Neighbourhood
Anita Sengupta
The Cybersecurity Control Playbook: From Fundamentals to Advanced Strategies
Jason Edwards
The Costume Designer's Toolkit The Process of Creating Effective Design
Holly Poe Durbin
The creative producing handbook
Katherine Beyda
Environmental Biotechnology : Fundamentals to Modern Techniques
Sibi G
Genocide in the Modern Age : State-Society Relations in the Making of Mass Political Violence
Zachary A. Karazsia
Digital Futures in Human-Computer Interaction : Design Thinking for Digital Transformation
Zhiyong Fu