[PDF.21fq] Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)

[PDF.bc15] Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)

Gaussian Processes for Machine  Carl Edward Rasmussen, Christopher K. I. Williams epub
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 | #141410 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

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||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 device.Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)   |  Carl Edward Rasmussen, Christopher K. I. Williams.Not only was the story interesting, engaging and relatable, it also teaches lessons.

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