Bokus
Pierre Bessiere, Emmanuel Mazer, Juan Ahuactzin, Kamel Mekhnacha - Bayesian Programming, E-bok

E-bok, Engelska, 2013

Bayesian Programming

Av Pierre Bessiere, Emmanuel Mazer, Juan Ahuactzin, Kamel Mekhnacha

Del i serien Chapman & Hall/CRC Machine Learning & Pattern Recognition

722 kr

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Beskrivning
A new modeling methodology, new inference algorithms, new programming languages, and new hardware are all needed to create a complete Bayesian computing framework. Focusing on the methodology and algorithms, this book describes the first steps toward reaching that goal. It emphasizes probability as an alternative to Boolean logic, covering new methods to build probabilistic programs for real-world applications. The book encourages readers to explore emerging areas and develop new programming languages and hardware architectures. A Python package is available on a supplementary website.
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Pierre Bessiere is with CNRS, the French National Centre for Scientific Research. Juan-Manuel Ahuactzin, Kamel Mekhnacha, and Emmanuel Mazer are with Probayes Inc., France.

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"Bayesian Programming comprises a methodology, a programming language, and a set of tools for developing and applying … complex models. … The approach is described in great detail, with many worked examples backed up by an online code repository. Unlike other books that tend to focus almost entirely on mathematics, this one gives equal time to conceptual and methodological guidance for the model-builder. It grapples with the knotty problems that arise in practice, some of which do not yet have clear solutions."—From the Foreword by Stuart Russell, University of California, Berkeley"The book has many worked examples backed up by an online code repository. The book provides a contibution on conceptual and methodological guidelines for model-builders. The authors discuss the problem how to build a Bayesian computer. The book has an excellent bibliography."—Nirode C. Mohanty, in Zentralblatt MATH 1281

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