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Now you have a bunch of data science models. Are their prescriptions consistent with one another?

What happens when more and more data science models make isolated decisions, sometimes at rapid rates, with
minimal or no explanations? Can multiple data science model responses be made to be consistent, collaborative,
transparent and yet be responsive?

What to expect

Team Composition

Technology platform engineers, End users of data science model prescriptions, Knowledge Engineers, Enterprise architects, Cloud partners

Benefits

Increased trust on model prescriptions, AI concepts adoption, Formulate and govern enterprise proprietary knowledge

Challenges

AI hype, Breadth of applicability of AI technology

Summary

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