You are asked rapid-fire ML fundamentals questions.
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What is overfitting?
Explain it in terms of training vs. validation performance and generalization.
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How can you prevent or mitigate overfitting?
List practical techniques and when you would use them.
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What is the difference between L1 and L2 regularization?
Compare their effect on model weights, feature selection, optimization behavior, and typical use cases.