Episode
AzureML Registries - Enabling Better Collaboration and MLOps
with Seth Juarez, Manoj Bableshwar
AzureML Registries is a new capability in AzureML that we are announcing at Ignite, October 12th. 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.
Join us every other Friday for an AI Show livestream on YouTube.
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
Recommended resources
- Share models, components and environments across workspaces with registries (preview)
- Manage Azure Machine Learning registries (preview)
- Announcing registries in Azure Machine Learning to operationalize models and pipelines at scale
Related episodes
Connect
- Seth Juarez | Twitter: @sethjuarez
AzureML Registries is a new capability in AzureML that we are announcing at Ignite, October 12th. 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.
Join us every other Friday for an AI Show livestream on YouTube.
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
Recommended resources
- Share models, components and environments across workspaces with registries (preview)
- Manage Azure Machine Learning registries (preview)
- Announcing registries in Azure Machine Learning to operationalize models and pipelines at scale
Related episodes
Connect
- Seth Juarez | Twitter: @sethjuarez
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