Bayesian Analysis with Python, 3rd Edition
A practical guide to probabilistic modeling
$71.85
- Paperback
394 pages
- Release Date
31 January 2024
Summary
Learn the fundamentals of Bayesian modeling using state-of-the-art Python libraries, such as PyMC, ArviZ, Bambi, and more, guided by an experienced Bayesian modeler who contributes to these libraries.
Key Features
- Conduct Bayesian data analysis with step-by-step guidance
- Gain insight into a modern, practical, and computational approach to Bayesian statistical modeling
- Enhance your learning with best practices through sample problems and…
Book Details
| ISBN-13: | 9781805127161 |
|---|---|
| ISBN-10: | 1805127160 |
| Author: | Osvaldo Martin, Christopher Fonnesbeck, Thomas Wiecki |
| Publisher: | Packt Publishing Limited |
| Imprint: | Packt Publishing Limited |
| Format: | Paperback |
| Number of Pages: | 394 |
| Edition: | 3rd |
| Release Date: | 31 January 2024 |
| Dimensions: | 191mm x 235mm |
Osvaldo Martin
Osvaldo Martin is a researcher at CONICET, in Argentina. He has experience using Markov Chain Monte Carlo methods to simulate molecules and perform Bayesian inference. He loves to use Python to solve data analysis problems. He is especially motivated by the development and implementation of software tools for Bayesian statistics and probabilistic modeling. He is an open-source developer, and he contributes to Python libraries like PyMC, ArviZ and Bambi among others. He is interested in all aspects of the Bayesian workflow, including numerical methods for inference, diagnosis of sampling, evaluation and criticism of models, comparison of models and presentation of results.
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