Gaussian Processes for Machine by Carl Edward Rasmussen (.PDF)
File Size: 2 MB
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series) by Carl Edward Rasmussen, Christopher K. I. Williams
Requirements: .PDF reader, 2 MB
Overview: 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.
Genre: Non-Fiction > Tech & Devices
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