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Introduction to machine learning /

紀錄類型:	書目-語言資料,印刷品 : 單行本
正題名/作者:	Introduction to machine learning // Ethem Alpaydin.
作者:	Alpaydin, Ethem,
出版者:	Cambridge, Massachusetts :The MIT Press,c2014.
面頁冊數:	xxii, 613 p. :ill. ;24 cm.
標題:	Machine learning. -
ISBN:	9780262028189 (hardcover) :
ISBN:	0262028182 (hardcover)

Introduction to machine learning /
Alpaydin, Ethem,

Introduction to machine learning /Ethem Alpaydin. - 3rd ed. - Cambridge, Massachusetts :The MIT Press,c2014. - xxii, 613 p. :ill. ;24 cm. - Adaptive computation and machine learning.

Includes bibliographical references (p. 203) and index.

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.

ISBN: 9780262028189 (hardcover) :NT1830

LCCN: 2014007214Subjects--Topical Terms:

147118
Machine learning.

LC Class. No.: Q325.5 / .A46 2014

Dewey Class. No.: 006.3/1

Introduction to machine learning /
LDR:01160cam a2200229 a 450 001 1000056213
005 20150402124832.0
008 140327s2014 maua b 001 0 eng
010 $a 2014007214
020 $a 9780262028189 (hardcover) : $c NT1830
020 $a 0262028182 (hardcover)
035 $a 18083265
040 $a DLC $b eng $c DLC
042 $a pcc
050 0 0 $a Q325.5 $b .A46 2014
082 0 0 $a 006.3/1 $2 23
100 1 $a Alpaydin, Ethem, $e author. $3 1000083170
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 0 $a Adaptive computation and machine learning
504 $a Includes bibliographical references (p. 203) and index.
505 0 # $a 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.
650 # 0 $a Machine learning. $3 147118

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