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Introduction to machine learning 3rd ed

Introduction to machine learning 3rd ed (Loan 46 times)

Material type
단행본
Personal Author
Alpaydin, Ethem.
Title Statement
Introduction to machine learning / Ethem Alpaydin.
판사항
3rd ed.
Publication, Distribution, etc
Cambridge, Massachusetts :   The MIT Press,   c2014.  
Physical Medium
xxii, 613 p. : ill. ; 24 cm.
Series Statement
Adaptive computation and machine learning
ISBN
9780262028189 (hardcover) 0262028182 (hardcover)
Content Notes
Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
Bibliography, Etc. Note
Includes bibliographical references (p. 203) and index.
Subject Added Entry-Topical Term
Machine learning.
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010 ▼a 2014007214
020 ▼a 9780262028189 (hardcover)
020 ▼a 0262028182 (hardcover)
035 ▼a (KERIS)REF000017709312
040 ▼a DLC ▼b eng ▼c DLC ▼e rda ▼d 211009
050 0 0 ▼a Q325.5 ▼b .A46 2014
082 0 0 ▼a 006.3/1 ▼2 23
084 ▼a 006.31 ▼2 DDCK
090 ▼a 006.31 ▼b A456i3
100 1 ▼a Alpaydin, Ethem.
245 1 0 ▼a Introduction to machine learning / ▼c Ethem Alpaydin.
250 ▼a 3rd ed.
260 ▼a Cambridge, Massachusetts : ▼b The MIT Press, ▼c c2014.
300 ▼a xxii, 613 p. : ▼b ill. ; ▼c 24 cm.
490 1 ▼a Adaptive computation and machine learning
504 ▼a Includes bibliographical references (p. 203) and index.
505 0 0 ▼g Introduction -- ▼t Supervised learning -- ▼t Bayesian decision theory -- ▼t Parametric methods -- ▼t Multivariate methods -- ▼t Dimensionality reduction -- ▼t Clustering -- ▼t Nonparametric methods -- ▼t Decision trees -- ▼t Linear discrimination -- ▼t Multilayer perceptrons -- ▼t Local models -- ▼t Kernel machines -- Graphical models -- ▼t Hidden markov models -- ▼t Bayesian estimation -- ▼t Combining multiple learners -- ▼t Reinforcement learning -- ▼t Design and analysis of machine learning experiments.
650 0 ▼a Machine learning.
830 0 ▼a Adaptive computation and machine learning.
945 ▼a KLPA

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 006.31 A456i3 Accession No. 121235995 Availability Available Due Date Make a Reservation Service B M
No. 2 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 006.31 A456i3 Accession No. 121238695 Availability Available Due Date Make a Reservation Service B M
No. 3 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 006.31 A456i3 Accession No. 121246546 Availability Available Due Date Make a Reservation Service B M

Contents information

Author Introduction

에템 알페이딘(지은이)

로잔공과대학에서 박사 학위를 받고 터키 이스탄불의 명문 보아지치대학교 컴퓨터공학과 교수로 재직 중이다. 세계적인 인공지능 전문가로 머신러닝을 전문적으로 연구하고 있다. 머신러닝 교과서로 널리 사용되고 있는 머신러닝 개론(Introduction to Machine Learning)의 저자다.

Information Provided By: : Aladin

Table of Contents

Intro -- Brief Contents -- Contents -- Preface -- Notations -- 1 Introduction -- 2 Supervised Learning -- 3 Bayesian Decision Theory -- 4 Parametric Methods -- 5 Multivariate Methods -- 6 Dimensionality Reduction -- 7 Clustering -- 8 Nonparametric Methods -- 9 Decision Trees -- 10 Linear Discrimination -- 11 Multilayer Perceptrons -- 12 Local Models -- 13 Kernel Machines -- 14 Graphical Models -- 15 Hidden Markov Models -- 16 Bayesian Estimation -- 17 Combining Multiple Learners -- 18 Reinforcement Learning -- 19 Design and Analysis of Machine Learning Experiments -- A Probability -- Index -- .

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