Probabilistic Libraries

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Probabilistic Libraries

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with PyTensor

PyMC (formerly PyMC3) is a Python package for Bayesian statistical modeling focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (VI) algorithms. Its flexibility and extensi…

Python code for "Probabilistic Machine learning" book by Kevin Murphy

The notebooks needed to make all the figures are available at the following locations. You can use any of the following options to install the other requirements. Run Then install manually.

UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.

To engage in conversations about uncertainty quantification, or ask question about UQpy usage and functionality refer to the UQpy's discussions tab: UQpy (Uncertainty Quantification with python) is a…

Free hands-on course with the implementation (in Python) and description of several computational, mathematical and statistical algorithms.

Free hands-on course with the implementation (in Python) and description of several computational, mathematical and statistical algorithms. Although it is not intended to have the formal rigor of a b…

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

This notebook contains the code required to conduct a Bayesian data analysis on data collected from a set of multiple-lot online auction events executed in Europen markets, over the course of a year.…

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