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Bayesian Modeling and Computation in Python (Hardcover) Loot Price: R2,383
Discovery Miles 23 830
Bayesian Modeling and Computation in Python (Hardcover): Osvaldo A. Martin, Ravi N Kumar, Junpeng Lao

Bayesian Modeling and Computation in Python (Hardcover)

Osvaldo A. Martin, Ravi N Kumar, Junpeng Lao

Series: Chapman & Hall/CRC Texts in Statistical Science

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Loot Price R2,383 Discovery Miles 23 830 | Repayment Terms: R223 pm x 12*

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Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying mathematical theory. The book starts with a refresher of the Bayesian Inference concepts. The second chapter introduces modern methods for Exploratory Analysis of Bayesian Models. With an understanding of these two fundamentals the subsequent chapters talk through various models including linear regressions, splines, time series, Bayesian additive regression trees. The final chapters include Approximate Bayesian Computation, end to end case studies showing how to apply Bayesian modelling in different settings, and a chapter about the internals of probabilistic programming languages. Finally the last chapter serves as a reference for the rest of the book by getting closer into mathematical aspects or by extending the discussion of certain topics. This book is written by contributors of PyMC3, ArviZ, Bambi, and Tensorflow Probability among other libraries.

General

Imprint: Crc Press
Country of origin: United Kingdom
Series: Chapman & Hall/CRC Texts in Statistical Science
Release date: December 2021
First published: 2022
Authors: Osvaldo A. Martin • Ravi N Kumar • Junpeng Lao
Dimensions: 254 x 178 x 23mm (L x W x T)
Format: Hardcover
Pages: 398
ISBN-13: 978-0-367-89436-8
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
LSN: 0-367-89436-X
Barcode: 9780367894368

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