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Statistical Learning Python Packages

Python packages with the GitHub topic statistical-learning. Sorted by relevance, with stars and monthly downloads.
BayesWitnesses
m2cgen

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

16K 3K 261
Techtonique
nnetsauce

Quasi-randomized (neural) networks

3K 20 4
Techtonique
mlsauce

Miscellaneous Statistical/Machine Learning tools

2K 11 2
Techtonique
bcn

Boosted Configuration Networks

1K 1 0
akomarla
expsmoothing

Exponential smoothing forecast model

1K 1 0
artemmavrin
stattools

Statistical learning and inference algorithms implemented in Python 3

1K 2 2
lightbluetitan
crimedatasets

The crimedatasets package provides a comprehensive collection of crime-related datasets from around the world. It includes extensive data on topics such as mass shootings, hate crimes, incarceration statistics, serial killers, corruption indexes, law enforcement data, criminal justice metrics, drug overdoses and more.

578 11 4
simon-hirsch
rolch

A package for online distributional learning.

542 35 7
simon-hirsch
ondil

Methods for online / incremental estimation of distributional regression models

530 34 7
yi-zhang
sthd

STHD: probabilistic cell typing of Single spots in whole Transcriptome spatial data with High Definition

234 38 8
JiaYaobo
fenbux

A Simple Statistical Distribution Library in JAX

225 16 0
iutzeler
skwdro

A Robust ML toolbox

213 21 1
semoglou
composite-silhouette

A robust clustering evaluation framework that combines micro- and macro-averaged silhouette scores into a composite metric using statistical weighting.

211 1 1
DeepanshS
mrinversion

Linear inversion of two-dimensional isotropic-anisotropic NMR correlation spectrum.

188 8 2
xRiskLab
woeboost

Weight of Evidence (WOE) Gradient Boosting

167 9 0
User10166
etec325library

Official Python Library for ETEC 325 – Applied Statistics. Published by the Department of Electrical & Computer Engineering Technology – New York Institute of Technology.

163 0 0
JCSadeghi
pyipm

Interval Predictor Models in Python

130 5 2
makeyourownmaker
mixupy

Python package for data augmentation inspired by Mixup: Beyond Empirical Risk Minimization

115 3 0
mscaudill
simplexers

Vector Projections onto Positive and Capped Simplices

66 0 0
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