Cover of Gaussian processes for machine learning

Gaussian processes for machine learning

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About “Gaussian processes for machine learning”

A book published in 2006. Gaussian processes (GPs) provide an approach to kernel-machine learning, and this book offers a comprehensive and self-contained treatment of theoretical and practical aspects of GPs in machine learning, targeted at researchers and students in machine learning and applied statistics.

Book details

First published
2006
Latest edition
2018 · ISBN 9780262256834
Pages
272
View more editions (6)
CoverEditionYearISBN
Gaussian Processes for Machine Learning20189780262256834Buy on Amazon
Gaussian Processes for Machine Learning20069781423769903Buy on Amazon
Gaussian processes for machine learning2006026218253XBuy on Amazon
Gaussian Processes for Machine Learning20059780262253321Buy on Amazon
Gaussian Processes for Machine Learning20059780262261074Buy on Amazon
Gaussian processes for machine learning2005026218253XBuy on Amazon

Frequently asked questions

How many pages is Gaussian processes for machine learning?

Gaussian processes for machine learning by Carl Edward Rasmussen has 272 pages.