Probabilistic Programming & Bayesian ML

Stanford NLP Python library for 100+ human languages. State-of-the-art neural pipelines for tokenization, NER, parsing, and sentiment analysis with pre-trained models. Apache 2.0 licensed.

Modern, comprehensive probabilistic programming framework in Python. Bayesian modeling with advanced MCMC sampling, variational inference, and seamless integration with ArviZ for visualization. Apache 2.0 licensed.

Exploratory analysis of Bayesian models with Python. Comprehensive visualization and diagnostics for probabilistic models, supporting PyMC, Pyro, Stan, and other PPLs. Apache 2.0 licensed.