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Tribuo, a Machine Learning Library for Java

github.com

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Re: Tribuo, a Machine Learning Library for Java

#5
post #2

Happy to answer any questions you may have about Tribuo.

What do you use to visualise results and explore features?

We're thinking about the visualisation story. At the moment we use notebooks with the IJava kernel to explore things (our tutorials are jupyter notebooks), but we're still working on the plotting angle.

Re: Tribuo, a Machine Learning Library for Java

#6
This looks excellent, will take a bit of time to go through and understand. The announcement blog is really helpful actually and explains the problem you're solving well (and one I am intimately familiar with so I see value here).

Congratulations!

Re: Tribuo, a Machine Learning Library for Java

#7
post #2

Happy to answer any questions you may have about Tribuo.

This looks really interesting! Kudos and thanks for the good work. Some questions:

- What does the future road map look like?

- Are you planning on adding more algorithms ?

- Any plans to bring in dataset and dataframe handling capabilities such as in numpy/pandas etc?

- What other interop features with other languages/platforms are planned?

- Any plans for AutoML features?

Re: Tribuo, a Machine Learning Library for Java

#9
post #7
post #2

Happy to answer any questions you may have about Tribuo.

This looks really interesting! Kudos and thanks for the good work. Some questions: - What does the future road map look like? - Are you planning on adding more algorithms ? - Any plans to bring in dataset and dataframe handling capabilities such as in numpy/pandas etc? - What other interop features with other languages/platforms are planned? - Any plans for AutoML features?

- 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.

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