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Everything about PyMC
Probabilistic programming library for the Python programming language
PyMC is a probabilistic programming library for Python. It can be used for Bayesian statistical modeling and probabilistic machine learning. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: PyMCA 5-minute orientation
- Pick up a classic book: Bayesian Analysis with PythonThe most-reprinted book on the subject
- Read the landmark paper: PyMC: a modern, and comprehensive probabilistic programming framework in PythonCited 691 times
- Go sideways: ArviZA closely related topic
- Go sideways: Stan (software)A closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
PyMC: a modern, and comprehensive probabilistic programming framework in Python
PyMC: Bayesian Stochastic Modelling inPython
Micellization, surface activities and thermodynamics study of dialkylpyridinium [C16pymCn][Br] (n = 1–4) in aqueous solutions
Bayesian Probabilistic Modeling applied to some environmental data using PyMC
PyMC-Marketing: Bayesian Marketing Mix Models and Customer Analytics in Python
Integrating Bayesian Inference into Structural Parameter Estimation: A Python-Based Approach Using OpenSeesPy and PyMC
📚 Books worth reading
Bayesian Analysis with PythonOsvaldo Martin · 2016
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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