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Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series) 1st Edition
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This landmark book provides a very extensive coverage of the field, ranging from basic representational issues to the latest techniques for approximate inference and learning. As such, it is likely to become a definitive reference for all those who work in this area. Detailed worked examples and case studies also make the book accessible to students.―Kevin Murphy, Department of Computer Science, University of British Columbia
- Grade level : 12 and up
- Item Weight : 4.7 pounds
- Hardcover : 1231 pages
- ISBN-10 : 0262013193
- ISBN-13 : 978-0262013192
- Dimensions : 9.22 x 8.18 x 2.05 inches
- Reading level : 18 and up
- Publisher : MIT Press; 1st edition (August 1, 2009)
- Language: : English
- Best Sellers Rank: #114,807 in Books (See Top 100 in Books)
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relevant chapters in Pattern Recognition and Machine learning by Bishop might be an easier starter, and you might learn more insight by just reading through. Come back to this book as this has much more detailed treatment, but be warned, it is very dry.
Is this book shipped from the actual publishers or a 3rd party vendor? Also, it'll be helpful to explicitly state the gray-scale print in description to manage expectations. Thanks.