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Additional “model conformance” approaches to support a larger variety of data scientist workflows and programming paradigms. For particular models, this approach streamlines the process for adding a new model into ModelOp Center by allowing data scientists to simply change their model’s input and output data structures to read from the ModelOp Center engine runtime “slots.” A typical paradigm that data scientists use to structure their code includes: (1) reading in data (2) processing and scoring the data (3) writing the inference out to a consuming application or data feed. Through this feature, data scientists need only make minor modifications to steps 1 and 3, using the intuitive ModelOp Center libraries. Note that ModelOp Center will continue to support the prior “conformance” approaches, which are still well suited for certain classes of models (e.g. explicit RESTful models). This capability includes support for:
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