Transformers for Tabular Data at Capital One with Bayan Bruss

EPISODE 591
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About this Episode

Today we’re joined by Bayan Bruss, a Sr. director of applied ML research at Capital One. In our conversation with Bayan, we dig into his work in applying various deep learning techniques to tabular data, including taking advancements made in other areas like graph CNNs and other traditional graph mining algorithms and applying them to financial services applications. We discuss why despite a “flood” of innovation in the field, work on tabular data doesn’t elicit as much fanfare despite its broad use across businesses, Bayan’s experience with the difficulty of making deep learning work on tabular data, and what opportunities have been presented for the field with the emergence of multi-modality and transformer models. We also explore a pair of papers from Bayan’s team, focused on both transformers and transfer learning for tabular data.

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Thanks to our sponsor Capital One

Capital One's AI and machine learning capabilities are central to how it builds products and services — and they're now at the forefront of what’s possible in banking. Whether helping consumers shop more safely online, giving customers new insights into their finances via award-winning mobile apps, or advancing research into cutting-edge applications of machine learning, Capital One is using technology to make banking better.
To learn more about Capital One's Machine Learning and AI efforts and research, visit twimlai.com/go/capitalone!
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