Mary Grace Moesta
Mary Grace Moesta is a senior data science consultant at Databricks. She's been working in the big data and data science space for several years with opportunities to collaborate across several verticals, with the majority of her work focused in the Retail and CPG space. Prior to Databricks, Mary Grace has been able to contribute to several machine learning applications namely - personalization use cases, forecasting, recommendation engines, and customer experience measures.
Sessions
Would you be better off deploying an ML model or the code that generates the model? This talk, targeted to practitioners, covers different deployment patterns for machine learning applications. Beyond introducing these patterns, we’ll discuss the downstream implications of each with respect to reproducibility, audit tracing, and CI/CD. To demonstrate solution driven architecture, we’ll lean on Delta and MLflow as core technologies to track lineage and manage the deployment strategy. The goal of this session is to empower practitioners to design efficient, automated, and robust machine learning systems.