Using MLflow and Databricks to Deploy ML Models in Production

Explore the world of Machine Learning Operations in this 58-minute conference talk by Ali Sezer from Databricks at the Data Science Festival. Discover how artificial intelligence has become a priority for most companies and learn how the ML Flow framework, coupled with Databricks Data Science offering, is helping teams build reliable systems for delivering models into production. Gain insights into implementing the ML Flow framework to manage your model development process end-to-end, obtaining a complete view of trained models, and structuring a production-grade model deployment strategy. Delve into complementary tools and features offered by Databricks, such as the Feature Store and AutoML, to enhance your machine learning workflows. Equip yourself with the knowledge to leverage ML flow and Databricks for efficient and effective deployment of ML models in production environments.

Using ML flow and Databricks to deploy ML models in Production - Data Science Festival