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Simplifying MLOps with Model Registry
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Presented by Meeta Dash - VP Product at Verta
To effectively deploy and scale ML models across the development pipeline requires a mix of machine learning, software engineering, and operational skills which is rare to find in a single person or even in a single team. Additionally, organizations with hundreds of models today face the unique challenge arising from the heterogeneity in ML workflows and the siloed nature of these teams.
To effectively deploy and scale ML models across the development pipeline requires a mix of machine learning, software engineering, and operational skills which is rare to find in a single person or even in a single team. Additionally, organizations with hundreds of models today face the unique challenge arising from the heterogeneity in ML workflows and the siloed nature of these teams.
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