Subject
3 entries
Probabilistic Programming
Bookmarks
Stochastic Volatility Modeling with PyMC
PyMC example notebook demonstrating stochastic volatility modeling — Bayesian inference for time-varying financial volatility using NUTS sampling. A showcase of what probabilistic programming makes tractable.
BayesDB
BayesDB from MIT CSAIL's probabilistic computing group — a database system that lets you query statistical relationships using a SQL-like language (BQL) without specifying a model. Automatically infers the right probabilistic model from data.
Bayesian Methods for Hackers
Cameron Davidson-Pilon's open-source book teaching Bayesian inference through computational examples in Python, using PyMC3 for probabilistic programming. The approach is computation-first rather than math-first — ideal for programmers who want to apply Bayesian reasoning without heavy statistics background.