Instruction: Describe why model explainability is important in the context of machine learning operations and how it can be achieved.
Context: This question is aimed at gauging the candidate's understanding of the role of explainability in building trust and transparency in machine learning models, a crucial element for models in production, particularly in regulated industries.
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The way I'd explain it in an interview is this: Explainability matters in MLOps because production support is not only about serving predictions. Teams need to debug failures, investigate incidents, communicate with stakeholders, and sometimes justify decisions in...
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