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Data Selection for Data-Centric AI: Data Quality Over Quantity // Cody Coleman // Coffee Sessions #59

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Towards Principled Machine Learning

There's a lot of missing pieces right here, where there's not super great tooling. You have to sort of a re configure that there are ther these sort of cascading effects when data changes. But i think the good news is that we can see kind of evidence of that in our insurance applications and stuff like that. There's something about being rather than just going with the likea quantity approach, to actually be more thoughtful. And i think that kind of thinking about like active learning, corset selection, these types of methods, whichiwould say are still very academic right now, but kind of keeping an eye on that.

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