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Podcast: DataFramed
Episode: #313 Developing Better Predictive Models with Graph Transformers with Jure Leskovec, Pioneer of Graph Transformers, Professor at Stanford
Description: The structured data that powers business decisions is more complex than the sequences processed by traditional AI models. Enterprise databases with their interconnected tables of customers, products, and transactions form intricate graphs that contain valuable predictive signals. But how can we effectively extract insights from these complex relationships without extensive manual feature engineering?Graph transformers are revolutionizing this space by treating databases as networks and learning directly from raw data. What if you could build models in hours instead of months while achieving better accuracy? How might this technology change the role of data scientists, allowing them...