"What are graph embeddings and why are they important?" This is one of the more common questions posed by graph data scientists in the field. In our Ask a Database video series, Data Science Solution Architect Katie Roberts explains that graph embeddings enable you to take the high-dimensional information that exists within your network structure and reduce that dimensionality into a format that you can use as input into other algorithms or ML models. Here from Katie about why this is important in this installment of our Ask a Data Scientist series.
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