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emquaszaabgybgcn – Read and download Carl Edward Rasmussen’s book Gaussian Processes for Machine Learning in PDF, EPub, Mobi, Kindle online. Book Gaussian Processes for Machine Learning by Carl Edward Rasmussen

Gaussian Processes for Machine Learning
by Carl Edward Rasmussen

Gaussian Processes for Machine Learning Carl Edward Rasmussen pdf
Gaussian Processes for Machine Learning Carl Edward Rasmussen pdf

Summary: A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes. show more

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Product details Format Hardback | 272 pages Dimensions 203 x 254 x 25mm | 726g Publication date 01 Dec 2005 Publisher MIT Press Ltd Imprint MIT Press Publication City/Country Cambridge, United States Language English ISBN10 026218253X ISBN13 9780262182539 Bestsellers rank 193,166

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