Many powerful Machine Learning algorithms are based on graphs, e.g., Page Rank (Pregel), Recommendation Engines (collaborative filtering), text summarization, and other NLP tasks.
There are even more applications once we consider data pre-processing and feature engineering which are both vital tasks in Machine Learning Pipelines.
In this workshop, we will overview the intersection of graphs and Machine Learning from Graph Analytics to Graph Neural Networks.
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