Machine Learning: A Probabilistic Perspective. Kevin P. Murphy

Machine Learning: A Probabilistic Perspective


Machine.Learning.A.Probabilistic.Perspective.pdf
ISBN: 9780262018029 | 1104 pages | 19 Mb


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Machine Learning: A Probabilistic Perspective Kevin P. Murphy
Publisher: MIT Press



Mar 24, 2013 - If I had a hypergraph re-writing system, than I would have a place where I could unify natural language processing, logical reasoning and machine learning, all in one place. Sep 7, 2013 - This series is self notes on the book Machine Learning: A Probabilistic Perspective written by Kevin P. Machine Learning: a Probabilistic Perspective Kevin Patrick Murphy. The note is mainly extracted from the book and plus my shallow opinions. Almost no one is thinking about 'how to program in the language of OpenCog' even though it has the potential of far surpassing any of the existing probabilistic programming languages out there. Dec 3, 2008 - For example, in statistical machine translation, alignment models are described with probability theory and fit to data, but their structure is complex enough that optimal inference is intractable, and how you do approximate inference (EM, Viterbi, beam search, etc.) is a very major issue. I'm struggling with getting a unified view, from all perspectives. It's a fantastic book I'm reading lately. Will Read Machine Learning Mitchell 适合初学者. But the most interesting differences Machine learning terms definitely sound pretty cool. May 11, 2013 - Will Read Data Mining: Practical Machine Learning Tools and Techniques 难度低使用. Maybe the perspective of computational intelligence lends itself to cool names.





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