TuringLang/Turing.jl
Bayesian inference with probabilistic programming.
This project helps researchers and data scientists build and analyze statistical models where uncertainties are explicitly handled. You provide data and a description of your model's assumptions, and it produces a range of plausible values for your model's parameters, along with estimates of their uncertainty. This is for anyone who needs to quantify uncertainty in their predictions or understand the range of possible outcomes from their data.
2,214 stars. Actively maintained with 4 commits in the last 30 days.
Use this if you need to build complex statistical models, especially when you have limited data or strong prior beliefs about the parameters, and want to incorporate uncertainty directly into your analysis.
Not ideal if you primarily need quick point estimates or simple descriptive statistics, or if you prefer a 'black box' machine learning approach without explicit model specification.
Stars
2,214
Forks
234
Language
Julia
License
MIT
Category
Last pushed
Mar 12, 2026
Commits (30d)
4
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/TuringLang/Turing.jl"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
CliMA/Oceananigans.jl
🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs
JuliaLang/julia
The Julia Programming Language
WassimTenachi/PhySO
Physical Symbolic Optimization
EnzymeAD/Enzyme.jl
Julia bindings for the Enzyme automatic differentiator
astroautomata/SymbolicRegression.jl
Distributed High-Performance Symbolic Regression in Julia