PyMC is a Python library for probabilistic programming focused on Bayesian statistical modeling and machine learning. Built on top of computational tools like Aesara and NumPy, PyMC allows users to define models using intuitive syntax and perform inference using MCMC, variational inference, and other advanced algorithms. It’s widely used in scientific research, data science, and decision modeling.
Features
- Define probabilistic models using Python syntax
- Bayesian inference with MCMC and VI
- Rich diagnostics and posterior analysis tools
- Supports custom distributions and likelihoods
- Integrates with NumPy, pandas, and JAX
- Visualization tools with ArviZ integration
Project Samples
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Apache License V2.0Follow PyMC
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