عنوان

Foundations of machine learning /

شابک

0262039400

شابک

9780262039406

عنوان اصلي

Foundations of machine learning /

نام عام مواد

[Book]

نام نخستين پديدآور

Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar.

وضعيت ويراست

Second edition.

محل نشرو پخش و غیره

Cambridge, Massachusetts :

نام ناشر، پخش کننده و غيره

The MIT Press,

تاریخ نشرو بخش و غیره

[2018]

نام خاص و کميت اثر

xv, 486 pages :

ساير جزييات

illustrations (some color) ;

ابعاد

24 cm.

عنوان فروست

Adaptive computation and machine learning

متن يادداشت

Includes bibliographical references and index.

متن يادداشت

The PAC learning framework -- Rademacher complexity and VC-dimension -- Model selection -- Support vector machines -- Kernel methods - Boosting -- On-line learning -- Multi-class classification -- Ranking -- Regression -- Maximum entropy models -- Conditional maximum entropy models -- Algorithmic stability -- Dimensionality reduction -- Learning automata and languages -- Reinforcement learning -- Conclusion -- Appendices: Linear algebra review ; Convex optimization ; Probability review ; Concentration inequalities ; Notions of information theory.

بدون عنوان

0

متن يادداشت

"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--Provided by publisher.

موضوع مستند نشده

Computer algorithms.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Computer algorithms.

موضوع مستند نشده

Künstliche Intelligenz.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Maschinelles Lernen.

شماره

ويراست

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Mohri, Mehryar

مستند نام اشخاص تاييد نشده

Rostamizadeh, Afshin

مستند نام اشخاص تاييد نشده

Talwalkar, Ameet

تاريخ عمليات

20200822104754.0

قواعد فهرست نويسي ( بخش توصيفي )

rda

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y