Join us for a guided introduction to MLflow Recipes, formerly MLflow Pipelines, as we dive into one of MLflow’s newest features. With the release of MLflow 2.0, MLflow Recipes received several upgrades and new features: AutoML, hyperparameter tuning, classification support, and much more. We’ll cover how MLflow Recipes fits into the larger ecosystem and work through setup and execution of your first MLflow Recipes project. We’ll wrap up the session with a quick Q&A.
Databricks
Sr. Software Engineer
Corey Zumar is a software engineer at Databricks, where he’s spent the last four years working on machine learning infrastructure and APIs for the machine learning lifecycle, including model development and production model management. Corey is an active developer of MLflow and leads open source MLflow development efforts at Databricks. He holds a master’s degree in computer science from UC Be…
Corey Zumar is a software engineer at Databricks, where he’s spent the last four years working on machine learning infrastructure and APIs for the machine learning lifecycle, including model development and production model management. Corey is an active developer of MLflow and leads open source MLflow development efforts at Databricks. He holds a master’s degree in computer science from UC Berkeley.
Databricks
Sr. Developer Advocate
Jim Hibbard is a Developer Advocate at Databricks. Prior to that, he worked at Seattle Children’s Hospital where he developed frameworks and methods for integrating medical records with multi-omics datasets to improve care. He is currently working on improving machine learning infrastructure and model management as part of the extended MLflow team.
Marketing Manager
Developer Advocate
Sr. Developer Advocate