Abstract: "MLOps" is a hot topic, as teams grapple with productionizing machine learning. Now, they need monitoring, lineage, deployment tools, not just modeling libraries. This talk introduces tools from Databricks, like open source MLflow and Delta, as well as a Feature Store, and how they help mitigate MLOps pain points.
Bio: Sean is a principal solutions architect focusing on machine learning and data science at Databricks. He is an Apache Spark committer and PMC member, and co-author Advanced Analytics with Spark. Previously, he was director of Data Science at Cloudera and an engineer at Google.