Productionize Machine Learning on Azure
summary
Describes Enterprise scale AI Factory that turns experiments into production with turnkey MLOps, AutoLake and reusable infra and pipeline templates. Claims: 97 bicep templates and 109 python files supply most boilerplate so teams configure not build. Landing zones take 4–16 hours, the AI Factory config takes ≈4 hours and a new project can auto-provision in ~30 minutes. Shows a working pipeline for tabular ML with retraining, drift detection and staged Dev→Stage→Prod promotion.
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chapters (9)
- 0:00Productionizing ML on Azure
- 4:02Moving ML to production
- 8:21Enterprise Scale AI Factory
- 13:52AI types and use cases
- 18:01Project setup and team onboarding
- 22:33MLOps and GenOps pipelines
- 25:20Data Lake design and structure
- 28:50Model performance evaluation
- 30:51AI Factory customization
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