Apache Big Data Seville 2016 – On the Representation and Reuse of Machine Learning Models – Villu Ruusmann

On the Representation and Reuse of Machine Learning Models – Villu Ruusmann

Big Data applications rely on machine learning to derive new value. Model training and deployment are handled by different people in different environments, which makes model transferability a major concern.

This talk inquires into popular R, Scikit-Learn and Apache Spark model types, and connects them at a standardized PMML representation level. PMML adds value to all stages of the workflow, starting from model interpretation, reorganization and persistence, and ending with fully-automated model deployment to schema-full Big Data frameworks.

Attendees will learn that models are not locked-in “black boxes”, but easily accessible and programmable components in the application layer. This realization should translate to improved workflows, and smarter and more performant applications.

More information about this talk

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