Finding the best model for a use case

The best for model for your usecase is the

1. trained on data closest to yours

2. trained for the same objective as yours

3. trained well (not overfit etc)

2 and 3 are easier to check

Possible algorithms for #1) (?)

how to compare the distance between your data and a dataset (L1/L2 norm)

how to do it fast

data distributions can be compared

how is data distribution defined for an image set?

for numerical dataset? defining it with range is too simple. Has to be some other characs, like this is radio data, so text description of data

how to programatically find the model(s) trained on datasets that includes your data