#scikit-learn

Fit interpretable models. Explain blackbox machine learning.

Survival analysis built on top of scikit-learn

Feature engineering and selection open-source Python library compatible with sklearn.

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

Base classes for creating scikit-learn-like parametric objects, and tools for working with them.

Extra blocks for scikit-learn pipelines.

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

MLeap: Deploy ML Pipelines to Production

End-to-end ML toolkit automating the complete workflow — data profiling, preprocessing, feature engineering, model selection, training, validation, explainability, drift monitoring, fairness checks, and interactive HTML reporting. Includes a full CLI for zero-code ML pipelines. Python 3.10+.

The scikit-learn-native foundation package for chemometrics 🧪 🤖

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs