Part 13/17:
Setting realistic accuracy thresholds is vital. While some require >95%, many business applications can benefit from lower thresholds if the insight provides value—e.g., 60-70% accuracy in certain detection tasks. Establishing proxy metrics, such as monitoring the gap between estimated and actual counts, enables ongoing performance assessment.
Monitoring & Explainability
Post-deployment, continuous observability is crucial. Tracking data and model drift, evaluating confidence scores, and implementing alert systems help maintain performance. Explaining AI decisions (explainability) builds trust and ensures compliance, especially in sensitive sectors like healthcare or finance.
Infrastructure Optimization
Balancing computational resources involves trade-offs: