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Bayesian Analysis with Python: A practical guide to probabilistic modeling - Softcover

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Synopsis

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 practice exercises
  • Purchase of the print or Kindle book includes a free PDF eBook.

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About the Author

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...

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  • PublisherPackt Publishing
  • Publication date2024
  • ISBN 10 1805127160
  • ISBN 13 9781805127161
  • BindingPaperback
  • LanguageEnglish
  • Edition number3
  • Number of pages394
  • Rating
    • 3.86 out of 5 stars
      7 ratings by Goodreads

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