| 000 | 00000cam u2200205 a 4500 | |
| 001 | 000045864972 | |
| 005 | 20160314163613 | |
| 008 | 160314s2014 maua b 001 0 eng d | |
| 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 |
| 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 |
| 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 |
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.
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 -- .