Foundations of Machine Learning, 2nd Edition
Book Details
| Authors | Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar |
| Publisher | MIT Press |
| Published | 2018 |
| Edition | 2 |
| Paperback | 505 pages |
| Language | English |
| ISBN-13 | 9780262039406 |
| ISBN-10 | 0262039400 |
| License | Creative Commons Attribution-NonCommercial-NoDerivatives |
Book Description
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 2nd 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.
This book is available under a Creative Commons Attribution-NonCommercial-NoDerivatives license (CC BY-NC-ND), which means that you are free to copy and distribute it, as long as you attribute the source, don't use it commercially, and don't create modified versions.
If you enjoyed the book and would like to support the author, you can purchase a printed copy (hardcover or paperback) from official retailers.
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