Machine Learning
51 bites tagged Machine Learning — interview questions with model answers, and 60-second explainers.
Architect a real-time multi-armed bandit and compare trade-offs to A/B testing
Sketch a fast arm router, streaming feedback, and model updates; contrast MAB regret minimization with A/B's unbiased estimates. Real-time ML serving and statistical trade-offs.
Outline an NLP pipeline to categorize reviews and identify pain points
Tests text mining pipeline design. Answers cover deduplication and normalization, then clustering or topic modeling for categories, plus sentiment analysis to rank pain points. Red flag: skipping validation or jumping to LLMs without cleaning.
Full Fine-Tuning: Updating Every Model Parameter
Full fine-tuning updates all weights of a pre-trained model on your new data, unlike methods that only change a small fraction. Use it to deeply embed new knowledge, but beware: it's costly and risks making the model forget its original general skills.
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