From Proof of Concept (POC) to Model as a Service (MAAS): Learning to Productionize On-Premise
This event will be Livestreamed.
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While Wells Fargo had known about the H2O platform for a while, we were limited to Proof of Concept/Technology (POC/T) projects. We knew eventually we would have to take a POJO or MOJO (H2O Optimized Model) and bring it into production. One aspect of working in machine learning at Wells Fargo is realizing that cloud and even packaged systems and libraries can be difficult to use for a variety of security regulation challenges. This meant a lot more design and planning was needed than we had envisioned. In this talk, I will take you through the processes we had to go through to design the workflow, data pipelines, historical feature generation, and MAAS related systems, all on premise. I’ll also discuss the processes we went through to bring models to production, and other technical considerations to bring a MOJO into a MAAS architecture that is able to be used internally.
Matthew Schlachtman is a Data Analyst at Wells Fargo.
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