AzureML Registries is a new capability in AzureML announched at Ignite. Registries are organization-wide repositories of Machine Learning assets such as Models, Environments and Components. Registries promote collaboration among data science teams by enabling discovery and reuse of ML models and related assets, improving productivity. Registries enable MLOps across dev, test and prod environments in which you need to promote assets across multiple AzureML workspaces. Today, we'll explore the pain points and challenges with multi-environment MLOps and how Registries can help overcome those.
Chapters:
00:00 Welcome to the AI Show
00:42 Welcome Manoj
00:58 What are Registries - Enterprise Machine Learning Lifecycle in the real world
04:45 Registries in Azure ML
05:15 Workspaces vs Registries
07:56 How to train the model
12:09 Register the model
18:17 Recap
19:36 Learn more
20:21 Wrap
Learn more:
https://aka.ms/AzureML/RegistryPreview
https://aka.ms/AzureML/Registries
https://aka.ms/Registries/Blog
Connect:
Seth | @Seth Juarez
Subscribe to the AI Show: https://aka.ms/AIShowsubscribe
AI Show Playlist: https://aka.ms/AIShowPlaylist
Join us every other Friday, for an AI Show livestream on YouTube https://aka.ms/AIShowLive