Tutorials

For a comprehensive theoretical and hands-on overview of KGE models and hands-on AmpliGraph, check out our ECAI-20 Tutorial (Slides + Recording + Colab Notebook).

The following Jupyter notebooks will guide you through the most important features of AmpliGraph:

• AmpliGraph basics: training, saving and restoring a model, evaluating a model, discover new links, visualize embeddings. [Jupyter notebook] [Colab notebook]
• Link-based clustering and classification: how to use the knowledge embeddings generated by a graph of international football matches in clustering and classification tasks. [Jupyter notebook] [Colab notebook]

Additional examples and code snippets are available here.