Wanted to do something involving ethereum and machine learning
What it does
Compares ethereum tokens by the graph embedding of their transaction network
How we built it
Uses a weighed sum of node2vec embeddings for graph of a particular token's transaction network to compute embedding for that token. Dataset created by using bigquery to query ethereum public dataset. Cosine similarity to compare graph embeddings.
Challenges we ran into