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