Discover strategies for streamlining AI DevOps processes using Model Registry in this 30-minute talk from the Toronto Machine Learning Series (TMLS). Explore how to overcome challenges in deploying and scaling ML models across development pipelines, addressing the need for diverse skills in machine learning, software engineering, and operations. Learn techniques to fast-track value creation and mitigate risks in your ML journey from development to production. Gain insights on ensuring model reproducibility and portability across various environments, and understand how to build transparency and governance through the implementation of a Model Registry. This presentation by Meeta Dash, VP Product at Verta, offers valuable knowledge for organizations managing numerous models and facing challenges related to heterogeneous ML workflows and siloed teams.
Overview
Syllabus
Simplifying AI DevOps with Model Registry
Taught by
Toronto Machine Learning Series (TMLS)
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