Productionizing Machine Learning with Apache Spark, MLflow and ONNX - Cloud Deployment Using SQL Server

Explore the challenges and solutions for productionizing machine learning in enterprise environments in this 26-minute video from Databricks. Learn how to manage the entire lifecycle of machine learning models using MLflow, an open-source platform for experimentation, reproducibility, and deployment. Discover the innovative approach of storing models in SQL Server as a model artifact store, treating models like data to leverage mission-critical features of data management. Gain insights into creating an ecosystem for harvesting analytical models, enabling data scientists and business analysts to discover and promote the best models. Understand how SQL Server simplifies model management by storing them as serialized varbinary objects, keeping models close to data, and streamlining the process for faster delivery and more accurate business insights. Explore the use of ONNX runtime in SQL, converting models to ONNX format, and deploying them on Edge for native predictions on data.

Introduction
Demo
Data Engineer
Application Developer
Summary