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Can an AI model anticipate how well it will perform in the wild?
> In many important applications, AI models are trained on labeled data but when deployed in the wild, labels are not readily available (for example in medical imaging where the model is identifying a cancerous patch, "ground-truth" labels may require expert examination). A critical question is -- in the absence of
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Can an AI model anticipate how well it will perform in the wild?
> In many important applications, AI models are trained on labeled data but when deployed in the wild, labels are not readily available (for example in medical imaging where the model is identifying a cancerous patch, "ground-truth" labels may require expert examination). A critical question is -- in the absence of
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https://deep.ghost.io/self-training-ensemblesCan an AI model anticipate how well it will perform in the wild?
> In many important applications, AI models are trained on labeled data but when deployed in the wild, labels are not readily available (for example in medical imaging where the model is identifying a cancerous patch, "ground-truth" labels may require expert examination). A critical question is -- in the absence of
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