Leading machine learning library.

Simple and efficient tools for predictive data analysis.

Accessible to everybody, and reusable in various contexts.

Skore is a Python open-source library created by Probabl, designed to help data scientists during model development. While scikit-learn sets the stage for scientific and engineering excellence, skore helps you find your path through the maze of experimentation.

Prepping tables for machine learning

• scikit-learn compatible
• Pandas and Polars dataframes inputs and outputs
• Work on heterogeneous types (numeric, categorical, dates, text, missing values...

Alternative and more secure way of persisting ML models, and tools to document models with their performance and limitations.

Survival and competing risk analysis, as a scikit-learn compatible library.

Imbalanced-learn offers a number of techniques commonly used in datasets showing strong between-class imbalance.

The most scikit-learn compatible library related to responsible AI. It has tools to monitor certain fairness related issues with the AI systems, and other tools to mitigate them.

Software platform implementing and extending the standards of the Semantic Web. It allows to create, manipulate, parse, serialize, query, reason and validate RDF data.

Joblib is a set of tools to provide lightweight pipelining in Python. It is optimized to be fast and robust on large data in particular and has specific optimizations for numpy arrays.