Dave Berenbaum

On second thought here, is it worthwhile to add sklearn integration? Since this is such a large framework, integration may be more complex, and if you have an opinion about...

sklearn is largely not focused on deep learning, which has been the primary use case for dvclive. Should other algorithms be supported? If the primary purpose is to track model...

This might require first making the current dvc integration more of a general abstraction.

Also related are the slides from yesterday's meetup: https://docs.google.com/presentation/d/1TfChy39Xb6vKVvuMaWihZjbYO97CRnESqd6-xdmbQV4/edit#slide=id.p. The whole presentation should be up soon in https://discord.gg/STQyxbU6. There was an example of using dvc experiments and then having a...

Agree this seems useful. Seems like there is some overlap with the dvc experiments api, which we have discussed refining and making public. Do you have any thoughts on whether...

Sounds good. I can imagine this expanding at some point to overlap more with dvc functionality (especially in connection with related issues like #141), but I agree that we should...

In this case, you not only want to keep an additional metric for the best value, but you might want to save the best model instead of the latest model,...

> @dberenbaum wouldn't that mean that we would somehow need to spercify what does "the best" mean? Yes. At least, it would probably entail specifying the metric to monitor and...

Great points! Users will probably rather reuse the existing functionality within those ML frameworks, and it fits better with the dvclive ethos of being lightweight and interfering with code as...

wandb now has support for something similar: https://docs.wandb.ai/guides/track/log#customize-the-summary. DVCLive could support something similar with either: 1. Granular best metrics like `live.log("loss", 0.2, keep="min")`. This could keep only the min loss...