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Community Team
Community Team

With graph data science, you can choose between several graph embedding algorithms, and generating low-dimensional vector spaces is easy. But how do you evaluate the embedding results in your machine learning application? Enter Emblaze, a Jupyter notebook widget for visually comparing embeddings developed by Carnegie Mellon University’s Data Interaction Group. In his tutorial, Nathan Smith shows you the power of the widget’s Python API to perform dimensionality reduction on multiple sets of embedding data and compare the embeddings using animated scatter plots.

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