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Machine learning refined : foundations, algorithms, and applications

Machine learning refined : foundations, algorithms, and applications

자료유형
단행본
개인저자
Watt, Jeremy. Borhani, Reza. Katsaggelos, Aggelos Konstantinos, 1956-.
서명 / 저자사항
Machine learning refined : foundations, algorithms, and applications / Jeremy Watt, Reza Borhani, Aggelos Katsaggelos.
발행사항
New York :   Cambridge University Press,   2016.  
형태사항
xiii, 286 p. : ill. (some col.) ; 26 cm.
ISBN
9781107123526 (hardback)
요약
"Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization"--Provided by publisher.
서지주기
Includes bibliographical references (p. [280]-284) and index.
일반주제명
Machine learning.
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020 ▼a 9781107123526 (hardback)
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245 0 0 ▼a Machine learning refined : ▼b foundations, algorithms, and applications / ▼c Jeremy Watt, Reza Borhani, Aggelos Katsaggelos.
260 ▼a New York : ▼b Cambridge University Press, ▼c 2016.
300 ▼a xiii, 286 p. : ▼b ill. (some col.) ; ▼c 26 cm.
504 ▼a Includes bibliographical references (p. [280]-284) and index.
520 ▼a "Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization"--Provided by publisher.
650 0 ▼a Machine learning.
700 1 ▼a Watt, Jeremy.
700 1 ▼a Borhani, Reza.
700 1 ▼a Katsaggelos, Aggelos Konstantinos, ▼d 1956-.

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 의학도서관/자료실(3층)/ 청구기호 006.31 M1494 등록번호 131051556 도서상태 대출가능 반납예정일 예약 서비스 B

컨텐츠정보

저자소개

Aggelos Katsaggelos(지은이)

Jeremy Watt(지은이)

Reza Borhani(지은이)

정보제공 : Aladin

목차

1. Introduction; Part I. The Basics: 2. Fundamentals of numerical optimization; 3. Knowledge-driven regression; 4. Knowledge-driven classification; Part II. Automatic Feature Design: 5. Automatic feature design for regression; 6. Automatic feature design for classification; 7. Kernels, backpropagation, and regularized cross-validation; Part III. Tools for Large Scale Data: 8. Advanced gradient schemes; 9. Dimension reduction techniques; Part IV. Appendices.


정보제공 : Aladin

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