Productionizing ML Models Using MLflow Model Serving

Explore the process of productionizing machine learning models using MLflow Model Serving in this 27-minute video from Databricks. Learn how to ensure model integrity, efficiently replicate runtime environments across servers, and track model creation. Discover the benefits of MLflow Model Serving for cost-effective, one-click deployment of models for real-time inferences. Cover key topics including deployment, consumption, and monitoring. Witness demonstrations of different version deployments, validation techniques, and connecting Power BI to generate prediction reports. Gain insights into managing MLflow serving, including access rights and monitoring capabilities. Understand the MLflow architecture, different model flavors, and strategies for improving accuracy in managed server models.

Introduction
Overview
About Me
Agenda
MLflow
MLflow Architecture
MLflow Model Serving
Different Flavors of Model
Demo
Serving
Improving Accuracy
Managed Server Models