Scikit Learn Python Packages

onnxruntime

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

dask

Parallel computing with task scheduling

onnx

Open standard for machine learning interoperability

skops

skops is a Python library helping you share your scikit-learn based models and put them in production

onnxruntime-gpu

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

mleap

MLeap: Deploy ML Pipelines to Production

skl2onnx

Convert scikit-learn models and pipelines to ONNX

sktime

A unified framework for machine learning with time series

interpret-core

Fit interpretable models. Explain blackbox machine learning.

scikit-optimize

Sequential model-based optimization with a `scipy.optimize` interface

onnxmltools

ONNXMLTools enables conversion of models to ONNX

autogluon-tabular

Fast and Accurate ML in 3 Lines of Code

flaml

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

autogluon-core

Fast and Accurate ML in 3 Lines of Code

autogluon-features

Fast and Accurate ML in 3 Lines of Code

autogluon-common

Fast and Accurate ML in 3 Lines of Code

kmodes

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

yellowbrick

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

betacal

Beta calibration

interpret

Fit interpretable models. Explain blackbox machine learning.

scikit-plot

An intuitive library to add plotting functionality to scikit-learn objects.

pycaret

Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.

onnx-weekly

Open standard for machine learning interoperability

aplr

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering smoother and interpretable predictions.