scikit-learn-contrib/MAPIE

Natural Gradient Boosting for Probabilistic Prediction

High-quality implementations of standard and SOTA methods on a variety of tasks.

A game theoretic approach to explain the output of any machine learning model.

Probabilistic reasoning and statistical analysis in TensorFlow

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

Uplift modeling and causal inference with machine learning algorithms

fklearn: Functional Machine Learning

⚡ TabPFN: Foundation Model for Tabular Data ⚡

scikit-learn: machine learning in Python