A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows;subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework;generalization bounds based on Rademacher complexity and VC-dimension;Support Vector Machines (SVMs);kernel methods;boosting;on-line learning;multi-class classification;ranking;regression;algorithmic stability;dimensionality reduction;learning automata and languages;and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review.This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.

Publisher: The MIT Press Language: English Print length: 504 pages Binding: Print length Dimensions: 9.1 x 7 x 1.2 inches Item weight: 2.71 pounds Best Sellers Rank (Amazon): 159401

Return Policy

1. Return Window
- Eligible for return within 30 days of delivery.

63. Return Conditions
- The book must be brand new (unused, unmarked, and undamaged).

Important Notes:
If the returned book is damaged or missing components, the refund may be denied. If the book arrives damaged (e.g., due to shipping issues), a full refund will be issued. For returns due to non-quality issues (e.g., buyer’s change of mind), the customer must cover return shipping costs.