Bayesian Modeling and Computation in Python Book Reviews
Bayesian Modeling and Computation in Python by Osvaldo A. Martin, Ravin Kumar & Junpeng Lao Book Summary
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.
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| Book Name | Bayesian Modeling and Computation in Python |
| Genre | Economics |
| Author | Osvaldo A. Martin, Ravin Kumar & Junpeng Lao |
| Published | 28 December 2021, Tuesday |
| Language | English |
| E-Book Size | 30.49 MB |
Bayesian Modeling and Computation in Python (Osvaldo A. Martin, Ravin Kumar & Junpeng Lao) Book Reviews 2024
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Summary of Bayesian Modeling and Computation in Python by Osvaldo A. Martin, Ravin Kumar & Junpeng Lao
The Bayesian Modeling and Computation in Python book written by Osvaldo A. Martin, Ravin Kumar & Junpeng Lao was published on 28 December 2021, Tuesday in the Economics category. A total of 142 readers of the book gave the book 0 points out of 5.
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