Model governance defines a collection of best practices for data science – versioning, reproducibility, experiment tracking, automated CI/CD, and others. Within a high-compliance setting where the data used for training or inference contains private health information (PHI) or similarly sensitive data, additional requirements such as strong identity management, role-based access control, approval workflows, and full audit trail are added.
This webinar summarizes requirements and best practices for establishing a high-productivity data science team within a high-compliance environment. It then demonstrates how these requirements can be met using John Snow Labs’ Healthcare AI Platform.
