
Transformers for Tabular Data at Capital One with Bayan Bruss - #591
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Challenges and Innovations in Tabular Data Models
This chapter explores the evolving landscape of machine learning techniques for tabular data, comparing traditional models like XGBoost with emerging deep learning methods. It discusses the potential of transfer learning and graph learning approaches to enhance performance across diverse datasets, particularly in fields like healthcare. The conversation underscores the need for improved tools and pre-trained models to simplify the application of deep learning in tabular data, highlighting both the challenges and opportunities present in this domain.
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