Machine Learning Operationalization
The lesson explains how ML Ops applies DevOps principles to machine learning, including infrastructure-as-code, version control, CI/CD pipelines, and automated workflows that trigger retraining when data changes and swap production models when quality improves.
This Module
Azure Machine Learning
Azure ML Compute and Data Management
Azure ML Workflow and Integration
Machine Learning Operationalization
Azure ML Workspaces and Access Control
Azure Machine Learning Studio
Demo: Exploring Azure ML Studio
Azure ML SDK, CLI, and Compute Instances
Demo: Visual Studio Code Integration
What is Automated Machine Learning?