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Introduction to machine learning

Author: Alpaydin, Ethem Series: Adaptive computation and machine learning Publisher: MIT Press, 2010.Edition: 2nd ed.Language: EnglishDescription: 537 p. : Graphs/Ill. ; 24 cm.ISBN: 9780262012430Type of document: BookBibliography/Index: Includes bibliographical references and index
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Item type Current location Collection Call number Status Date due Barcode Item holds
Book Europe Campus
Main Collection
Print Q325 .A57 2010
(Browse shelf)
001272673
Available 001272673
Total holds: 0

Includes bibliographical references and index

Digitized

Introduction to Machine Learning Brief Contents 1 Introduction 1 21 47 87 109 163 209 233 309 341 387 419 447 475 2 Supervised Learning 3 Bayesian Decision Theory 4 Parametric Methods 61 5 Multivariate Methods 6 Dimensionality Reduction 7 Clustering 143 8 Non parametric Methods 9 Decision Trees 185 10 Linear Discrimination 11 Multilayer Perceptrons 12 Local Models 13 Kernel Machines 279 14 Bayesian Estimation 16 Graphical Models 18 Reinforcement Learning A Probability 517 15 Hidden Markov Models 363 17 Combining Multiple Learners 19 Design and Analysis of Machine Learning Experiments

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