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When might overfitting and underfitting occur in a real-world setting? What are some of the effects these occurrences can have on model accuracy and performance?

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Interview question asked to Machine Learning Engineers interviewing at Arm, Amazon, GitHub and others: When might overfitting and underfitting occur in a real-world setting? What are some of the effects these occurrences can have on model accuracy and performance?.