[PDF.13co] Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)
Download PDF | ePub | DOC | audiobook | ebooks
Home -> Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series) free download
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)
Carl Edward Rasmussen, Christopher K. I. Williams
[PDF.vv84] Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)
Gaussian Processes for Machine Carl Edward Rasmussen, Christopher K. I. Williams epub Gaussian Processes for Machine Carl Edward Rasmussen, Christopher K. I. Williams pdf download Gaussian Processes for Machine Carl Edward Rasmussen, Christopher K. I. Williams pdf file Gaussian Processes for Machine Carl Edward Rasmussen, Christopher K. I. Williams audiobook Gaussian Processes for Machine Carl Edward Rasmussen, Christopher K. I. Williams book review Gaussian Processes for Machine Carl Edward Rasmussen, Christopher K. I. Williams summary
| #486231 in Books | imusti | 2005-11-23 | Original language:English | PDF # 1 | 10.00 x.75 x8.00l,1.65 | File type: PDF | 272 pages | Mit Press||11 of 13 people found the following review helpful.| Easily worth three times its price.|By Steven B.|Even though this is not a cookbook on Gaussian Processes, the explanations are clear and to the point.
The book is highly technical but it also does a great job explaining how Gaussian Processes fit in the big picture regarding the last few decades in the Machine Learning field and how they are related in some ways t||||About the Author||Carl Edward Rasmussen is a Lecturer at the Department of Engineering, University of Cambridge, and Adjunct Research Scientist at the Max Planck Institute for Biological Cybernetics, Tübingen.
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...
You easily download any file type for your gadget.Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series) | Carl Edward Rasmussen, Christopher K. I. Williams. I really enjoyed this book and have already told so many people about it!
