Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Ggstatsplot | 1,860 | 1 | 4 | 2 months ago | 40 | August 07, 2023 | 62 | gpl-3.0 | R | |
Enhancing {ggplot2} plots with statistical analysis 📊📣 | ||||||||||
Imodels | 1,229 | 4 | 3 months ago | 44 | October 05, 2023 | 27 | mit | Jupyter Notebook | ||
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible). | ||||||||||
Easystats | 987 | 3 months ago | 3 | November 05, 2023 | 43 | other | R | |||
:milky_way: The R easystats-project | ||||||||||
Bayeslite | 828 | 4 years ago | 193 | apache-2.0 | Python | |||||
BayesDB on SQLite. A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself. | ||||||||||
Lightweight_mmm | 701 | 3 months ago | 11 | June 30, 2022 | 93 | apache-2.0 | Python | |||
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information. | ||||||||||
Statistical Rethinking With Python And Pymc3 | 674 | 6 years ago | 2 | Jupyter Notebook | ||||||
Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath | ||||||||||
Pecan | 193 | 2 months ago | 452 | other | R | |||||
The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox. | ||||||||||
Probflow | 108 | 3 years ago | 12 | December 28, 2020 | 16 | mit | Python | |||
A Python package for building Bayesian models with TensorFlow or PyTorch | ||||||||||
Toolbox | 104 | 3 years ago | 46 | apache-2.0 | Java | |||||
A Java Toolbox for Scalable Probabilistic Machine Learning | ||||||||||
Birch | 101 | 6 months ago | 3 | apache-2.0 | C++ | |||||
A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods. |