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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
StellarGraph - Machine Learning on Graphs
| Date | Stars |
|---|---|
| 2026-07-31 | 3061 |
| 2026-08-03 | 3061 |
| 2026-08-04 | 3061 |
| 2026-08-06 | 3060 |
| 2026-08-13 | 3060 |
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| 2026-09-03 | 3059 |
| 2026-09-07 | 3058 |
| 2026-09-13 | 3059 |
| 2026-09-14 | 3058 |
| 2026-09-16 | 3058 |
| 2026-09-20 | 3058 |
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# StellarGraph Machine Learning Library
**StellarGraph** is a Python library for machine learning on [graphs and networks](https://en.wikipedia.org/wiki/Graph_%28discrete_mathematics%29).
## Table of Contents
* [Introduction](#introduction)
* [Getting Started](#getting-started)
* [Getting Help](#getting-help)
* [Example: GCN](#example-gcn)
* [Algorithms](#algorithms)
* [Installation](#installation)
* [Install StellarGraph using PyPI](#install-stellargraph-using-pypi)
* [Install StellarGraph in Anaconda Python](#install-stellargraph-in-anaconda-python)
* [Install StellarGraph from GitHub source](#install-stellargraph-from-github-source)
* [Citing](#citing)
* [References](#references)
## Introduction
The StellarGraph library offers state-of-the-art algorithms for [graph machine learning](https://medium.com/stellargraph/knowing-your-neighbours-machine-learning-on-graphs-9b7c3d0d5896), making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks:
- Representation learning for nodes and edges, to be used for visualisation and various downstream machine learning tasks;
- [Classification and attribute inference of nodes](https://medium.com/stellargraph/can-graph-machine-learning-identify-hate-speech-in-online-social-networks-58e3b80c9f7e) or edges;
- Classification of whole graphs;
- Link prediction;
- [Interpretation of node classification](https://medium.com/stellargraph/https-medium-com-stellargraph-saliency-maps-for-graph-machine-learning-5cca536974da) [8].
Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can contain people as nodes and friendships between them as links, with data like a person's age and the date a friendship was established. StellarGraph supports analysis of many kinds of graphs:
- homogeneous (with nodes and links of one type),
- heterogeneous (with more than one type of nodes and/or links)
- knowledge graphs (extreme heterogeneous graphs with thousands of types of edges)
- graphs with or without data associated with nodes
- graphs with edge weigExcerpt of 21,582 characters
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Huon Wilson · @clipboard-app · Australia
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:be1313d0e3445fb8, llm:Repository topics and description: 'Machine Learning on Graphs', topics include graph-neural-networks, graph-convolutional-networks, gcn, geometric-deep-learning, link-prediction, graph-machine-learning, graph-analysis; README: 'StellarGraph is a Python library for machine learning on graphs and networks.'
matched fp:be1313d0e3445fb8, llm:Repository topics and description: 'Machine Learning on Graphs', topics include graph-neural-networks, graph-convolutional-networks, gcn, geometric-deep-learning, link-prediction, graph-machine-learning, graph-analysis; README: 'StellarGraph is a Python library for machine learning on graphs and networks.'
matched fp:be1313d0e3445fb8, llm:Repository topics and description: 'Machine Learning on Graphs', topics include graph-neural-networks, graph-convolutional-networks, gcn, geometric-deep-learning, link-prediction, graph-machine-learning, graph-analysis; README: 'StellarGraph is a Python library for machine learning on graphs and networks.'