The Power of Framework Dimensions: What Data Scientists Should Know
A previous article provided a of conceptual frameworks – analytical structures for representing abstract concepts and organizing data. Data scientists use such frameworks in a wide variety of contexts, from use case ideation and validation of machine learning models to productization and operation of user-facing solutions. The framework type (e.g., hierarchy, matrix, process flow, relational …
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