Techniques to Improve Model Output (20%)
Model Evaluation
KEY CONCEPTS
- →Automatic metrics: BLEU, ROUGE, perplexity
- →Human evaluation importance
- →Task-specific evaluation criteria
- →A/B testing in production
- →Model monitoring for drift detection
WHAT THE EXAM IS REALLY TESTING
Understand that automatic metrics have limitations. Human evaluation remains critical for quality assessment.
COMMON TRAPS
- !Over-relying on automatic metrics
- !Not establishing evaluation criteria upfront
- !Ignoring task-specific quality requirements
OFFICIAL DOCUMENTATION
PRACTICE QUESTIONS
3 questions available for this topic
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