Matthew Tovbin
Matthew Tovbin
**Problem** Prepping release notes is a boring process. **Solution** Let's add [release-drafter ](https://github.com/release-drafter/release-drafter) to help us do it quicker. **Alternatives** Keep doing it manually which is meh. **Additional context** No...
**Problem** Currently `FeatureBuilder.fromDataFrame` only infers a set of primitive TransmogrifAI types directly mapped from dataframe schema, such as `Text`, `Real` etc. But more advanced types, such as `PickList`, `Email`, `Phone`...
**Problem** We would like to be able to store some types of metadata of the level of the model, e.g instance holdout splits. Currently there is no easy way to...
**Problem** We would like to be able to treat GeoLocation values as categorical features. **Solution** Add unary transformer to convert `Geolocation` values into `Country`. **Alternatives** N/A
**Problem** TransmogrifAI is currently only usable from Scala with Spark. It would be great if one could: 1. Load TransmogrifAI models in Python, display model insights and compare/evaluate with other...
**Problem** Too lazy to merge approved PRs? **Solution** Look no further. Enable Mergify - https://github.com/marketplace/mergify **Alternatives** N/A
**Problem** Exported models neither have any version information nor verification checks (on loading) that verify that a particular model can be safely executed with the current code version. **Solution** 1....
**Problem** Some of our transformers & estimators are not thoroughly tested or not tested at all. **Solution** Use `OpTransformerSpec` and `OpEstimatorSpec` base test specs to provide tests for all existing...
**Problem** Currently there is no standard way for users to test out their readers, features, workflows and apps. **Solution** Similarly to `OpTransformerSpec` and `OpEstimatorSpec` we provide test facilities to allow...
**Problem** Currently there is no type checks available to allow response / predictor specific feature engineering. For instance for response feature of type `FeatureLike[RealNN]` it makes sense to have `feature.calibrate`...