David de la Iglesia Castro

For reference, `comet.ml` has a built-in integration with `mlflow`: https://www.comet.ml/docs/python-sdk/mlflow/ It just requires adding `import comet_ml` to the script where `mlflow` is being used. It seems to capture existing `mlflow.log*`...

> 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...

Added https://aimstack.io/ to the list

> Added https://aimstack.io/ to the list Conversions from TensorBoard and MLFlow https://aimstack.readthedocs.io/en/latest/quick_start/convert_data.html

> Do you have any thoughts on whether one would be more helpful than another? I guess that it depends on whether we want `dvc` to be a mandatory dependency...

> As to problems: > Related: #81 - both in this issue and here we need to come up with a way to store the data in a structured way....

> Yeah, but before implementing that we need to consider how do we want to handle it on DVC side - if we include those in summary json, those values...

I was trying an example repo with `dvclive` using `dvc expepriments` where the pipeline some stages after the `train` stage (where `dvclive` is actually used) that depend on selecting the...

> 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...

> If dvclive had an option similar to `restore_best_weights`, the full pipeline could run automatically since the model file from the latest checkpoint would always be the best. It also...