Enterprise Model Governance
Jordan discusses the importance of an enterprise-wide data catalog that tracks modeling work and data usage. He emphasizes the need for collaboration to integrate models and software applications into the data governance lifecycle for better transparency and control.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Jordan Edwards: ML Engineering and DevOps on AzureML
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