sknetwork-team/scikit-network

What it solves

It provides a memory-efficient way to perform machine learning and analysis on graphs, offering fast algorithms and a simple API for handling complex network data.

How it works

The library represents graphs as sparse matrices using the scipy format, which allows it to process large networks while minimizing memory usage. It follows a design philosophy inspired by scikit-learn, making it intuitive for users familiar with the rest of Python's machine learning ecosystem.

Who it’s for

Data scientists and researchers who need to analyze network structures and apply machine learning techniques to graph-based data.

Highlights

• Memory-efficient graph representation using sparse matrices.
• Fast algorithm implementations.
• API design inspired by scikit-learn for ease of use.