Pymc3

PyMC (formerly known as PyMC3) is a modern, open-source probabilistic programming library in Python used for Bayesian statistical modeling and advanced data analysis. It enables users to build complex probabilistic models using intuitive syntax and perform inference using state-of-the-art sampling algorithms.

• Powerful probabilistic programming library for Bayesian modeling and inference.
• Built on top of Python with strong integration with NumPy, SciPy, and Pandas.
• Supports advanced sampling methods like MCMC and NUTS.
• Flexible model specification using intuitive and readable syntax.
• High-performance computation using modern backend libraries.
• Widely used in data science, research, and machine learning workflows.

PyMC Usage:

$ source pymc-env/bin/activate
$ python -c "import pymc; print(pymc.__version__)"
  

Disclaimer: PyMC is an open-source Python library maintained by its community and contributors. It is not a standalone application or cloud service but a programming library used within Python environments for statistical modeling and machine learning. Users should ensure proper environment setup and dependency management before using it in production.