Machine Learning Fundamentals › Overfitting & Underfitting

What are best practices for Overfitting & Underfitting

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Answer

Use techniques like cross validation, regularization, and simpler models when data is limited, and always compare training performance against testing performance to catch these issues early.

Real-world example A student who memorizes exact exam questions without understanding the topic is like an overfit model, while a student who barely studies at all is like an underfit model.

Common follow-ups: What is regularization, What is the bias variance tradeoff, What is cross validation

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