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电面就是个系统设计, 根据whiteboard记录整理:
* How would you diagnose a spam classifier with high offline accuracy but poor production performance?
* If recall is low, how would you perform EDA and analyze false negatives?
* What features would you use to train a new spam/job-quality classifier?
* How does widespread LLM-generated content change your approach?
* How would you defend an LLM-based classifi determine whether the new model is statistically better?
* What does a p-value mean?
* How would you monitor the model after full deployment?
* How would you quantify data drift and concept drift? |