Today we are pleased to announce the availability of Tribuo, a Java Machine Learning (ML) library, as open source. We’re releasing it under an Apache 2.0 license on Github for the wider ML community to use.
In Oracle Labs‘ Machine Learning Research Group, we’ve been working on deploying Machine Learning (ML) models into large production systems for years. During this time we’ve noticed a crucial gap between the expectations of an enterprise system, and the features provided by most ML libraries. Large software systems want to use building blocks which describe themselves and know when their inputs or outputs are invalid.
In contrast, most ML libraries expect a pile of float arrays to train a model. Then at deployment time, they expect the input to be a float array, and they produce yet another float array as the predicted output. The description of what any of these arrays mean, or what the input/output floats should look like, is left to another system, either a wiki, a bug tracker, or written as a code comment. We don’t think developers want to add yet another database table per ML model just to explain what that array of output floats means. Read the complete article here.
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