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Introduction to machine learning

Author: Ethem Alpaydin
Publisher: Cambridge, Mass. : MIT Press, ©2004.
Series: Adaptive computation and machine learning.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
"This book can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods."--Jacket.
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Ethem Alpaydin
ISBN: 0262012111 9780262012119
OCLC Number: 56830710
Description: xxx, 415 pages : illustrations ; 24 cm.
Contents: Supervised learning --
Bayesian decision theory --
Parametric methods --
Multivariate methods --
Dimensionality reduction --
Clustering --
Nonparametric methods --
Decision trees --
Linear discrimination --
Multilayer perceptrons --
Local models --
Hidden Markov models --
Assessing and comparing classification algorithms --
Combining multiple learners --
Reinforcement learning --
Probability.
Series Title: Adaptive computation and machine learning.
Responsibility: Ethem Alpaydın.
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Abstract:

An introductory text in machine learning that gives a unified treatment of methods based on statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and  Read more...

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