Search Packages

yellowbrick

Visual analysis and diagnostic tools to facilitate machine learning model selection.

sklearndf

DataFrame support for scikit-learn.

dynesty

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

evalml

EvalML is an AutoML library written in python.

ultranest

Fit and compare complex models reliably and rapidly. Advanced nested sampling.

shap-hypetune

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

gamma-facet

Human-explainable AI.

hyperactive

A unified interface for optimization algorithms and experiments

sklearn-genetic-opt

ML hyperparameters tuning and features selection, using evolutionary algorithms.

tscv

Time series cross-validation

bxa

Bayesian X-ray analysis (nested sampling for Xspec and Sherpa)

petab-select

Model selection for PEtab

lazygrid

Automatic, efficient and flexible implementation of complex machine learning pipeline generation and cross-validation.

dissectml

The missing middle layer between EDA and AutoML — unified pipeline from deep data understanding to model comparison in 3 function calls. Deep EDA, 36-model battle arena, statistical significance testing, target leakage detection, and publication-ready HTML reports.

cascade-ml

Lightweight and modular MLOps library targeted at small teams or individuals

tpot2

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

greybox

Toolbox for model building and forecasting

bayesloop

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

kulprit

Kullback-Leibler projections for Bayesian model selection in Python

estyp

Extended Statistical Toolkit Yet Practical

insurance-cv

Temporal and distributional cross-validation, and feature screening, for insurance pricing models

easymlselector

A model selection process for Machine Learning tasks on subset of training sample

fluidml

FluidML is a lightweight framework for developing machine learning pipelines. Focus only on your tasks and not the boilerplate!