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

skl2onnx

Convert scikit-learn models and pipelines to ONNX

mleap

MLeap: Deploy ML Pipelines to Production

sktime

A unified framework for machine learning with time series

interpret-core

Fit interpretable models. Explain blackbox machine learning.

onnxmltools

ONNXMLTools enables conversion of models to ONNX

scikit-optimize

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

onnxruntime-openvino

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

kmodes

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

flaml

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

yellowbrick

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

autogluon-core

Fast and Accurate ML in 3 Lines of Code

scikit-plot

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

autogluon-features

Fast and Accurate ML in 3 Lines of Code

autogluon-tabular

Fast and Accurate ML in 3 Lines of Code

autogluon-common

Fast and Accurate ML in 3 Lines of Code

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.

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

scikit-survival

Survival analysis built on top of scikit-learn