| #58902 in Books | Koller Daphne Friedman Nir | 2009-07-31 | Original language:English | PDF # 1 | 9.00 x1.69 x8.00l,4.65 | File type: PDF | 1270 pages | Probabilistic Graphical Models Principles and Techniques||0 of 0 people found the following review helpful.| Suboptimal writing style (judging by first few chapters)|By Matan|Judging by the first few chapters, the text is cumbersome and not as clear as it could have been under a more disciplined writing style; Sentences and paragraphs are longer than they should be, and the English grammar is most of the time improper or just a little odd. Reads too much like a transcript of a free sp|||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 th
Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually c...
You can specify the type of files you want, for your gadget.Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series) | Daphne Koller, Nir Friedman. I have read it a couple of times and even shared with my family members. Really good. Couldnt put it down.
