Data Correlation Insights
Matt discusses the importance of clean data in building predictive models, emphasizing that repeated use of validation data can lead to misleading results. He highlights how different predictive tasks require varying amounts of data, and Neil points out the inherent biases in tournament seeding, which can contribute to unexpected outcomes. The conversation reveals that the data used by seeding committees is often limited, suggesting that a more comprehensive dataset could lead to better predictions.In this clip
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StarTalk Podcast: Cosmic Queries – Rise of the Machines with Matt Ginsberg
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