tribuo

We built model & data provenance into our open source ML library, though it's admittedly not the W3C PROV standard. There were a few gaps in it until we built an automated reproducibility system on top of it, but now it's pretty solid for all the algorithms we implement. Unfortunately some of the things we wrap (notably TensorFlow) aren't reproducible enough due to some unfixed bugs. There's an overview of the provenance system in this reprise of the JavaOne talk I gave here https://www.youtube.com/watch?v=GXOMjq2OS_c. The library is on GitHub - https://github.com/oracle/tribuo.

You can with some hoop jumping in the current release (e.g. using 1.14 you need to define the model and optimizer in Python - https://github.com/oracle/tribuo/blob/main/Interop/Tensorflo...). With the upcoming alpha release from the TF Java group you can train purely from Java without invoking any Python - https://github.com/tensorflow/java-models/blob/master/tensor...

- Short term roadmap is here - https://github.com/oracle/tribuo/blob/main/docs/Roadmap.md, longer term we'd like to see what the community wants. - Yep. - There are various efforts on the JVM to build multidimensional arrays, we're talking to many of them to try and figure out a strategy for the whole platform. Ditto for dataframes, though Apache Arrow looks like a good baseline. - We're not looking at other languages outside of the JVM at the moment, but we're continuing to contribute to Tensorflow Java and ONNX Runtime to improve their Java support. We could look at pytorch inference support based on their Java API, but that overlaps pretty well with the things that ONNX Runtime supports. Do you have any suggestions? - Not beyond hyperparameter tuning.

Tribuo is a library for Machine Learning, written in Java, which supports classification, regression, clustering, anomaly detection, along with deep learning support via TensorFlow and ONNX. Tribuo has a strong focus on model metadata & tracking through it’s provenance system, supports loading third party models including those trained in Python packages like scikit-learn, and provides a variety of ML algorithms implemented in Java. Jupyter notebook based tutorials (statically hosted on the website - https://tribuo.org/learn/4.0/tutorials/, and the notebooks themselves on github - https://github.com/oracle/tribuo/tree/main/tutorials).