Your question is Loss Function Trade-Offs. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Can you explain the trade-offs between different loss functions in your previous machine learning projects? Discuss how you selected a loss function for the prediction objective, including its effects on optimization, outliers or mislabeled data, class imbalance, calibration, and the evaluation metric. Demonstrate the comparison with production-quality Python on a tabular classification dataset, using a fixed validation protocol and explaining which loss you would deploy and why.