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    The Role of Containers on MLOps and Model Production

    Container technology has changed the way data science gets done. The original container use case for data science focused on what I call, “environment management”....

    On Being Model-driven: Metrics and Monitoring

    This article covers a couple of key Machine Learning (ML) vital signs to consider when tracking ML models in production to ensure model reliability,...

    Product Management for AI

    Pete Skomoroch presented “Product Management for AI” at Rev. This post provides a distilled summary, video, and full transcript. Session Summary Pete...

    Themes and Conferences per Pacoid, Episode 7

    Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Introduction Welcome back...

    Model Evaluation

    This Domino Data Science Field Note provides some highlights of Alice Zheng’s report, "Evaluating Machine Learning Models", including evaluation...

    Managing Data Science as a Capability

    Nick Elprin, CEO at Domino, presented a 3-hour training workshop, “Managing Data Science in the Enterprise”, that provided practical insights and...

    Data Quality Analytics

    Scott Murdoch, PhD, Director of Data Science at HealthJoy, presents how data scientists can use distribution and modeling techniques to understand...