[sourabh03agr]

Completely agree! We have also seen our users more concerned about comparing the real-world distribution against the training data as compared to previous month's data (we found latter is more useful for PMs and setting alerts).

We currently allow users to specify their training data in the config which is used to initialise the UpTrain framework (in form of json file but are planning to support pytorch/tf data-loaders). In the background, the tool does all the binning and clustering to convert these continuous variables into discrete buckets to later calculate divergence, which is then used to quantify drift.