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DataPerf is an MLCommons benchmark system for measuring dataset quality for particular purposes, analogous to model benchmarks. How should we leverage it or even contribute to it as part of our efforts to create trusted datasets?
This is an interesting idea, but the current approach seems to be a bit limited. It seems to only get the best sellers, assuming that they all provide similar data. I think this is not exactly what we are looking for. In my mind, we are more interested in the data quality evaluation, that they do not seem to have in their project. So using their project as is does not seem feasible.
The option to consider there is to try to join forces with them to tackle data quality challenges, assuming that this is something that they are interested in doing
DataPerf is an MLCommons benchmark system for measuring dataset quality for particular purposes, analogous to model benchmarks. How should we leverage it or even contribute to it as part of our efforts to create trusted datasets?
See also this TSEI task #40
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