Your question is Handling Imbalanced Data. 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).
How do you handle imbalanced datasets?
Explain how you would diagnose the imbalance, prepare the training data, select an appropriate model and loss function, choose evaluation metrics, and set an operating threshold. Address when you would use class weighting, resampling, or synthetic sampling, and how you would prevent validation leakage. Include production considerations such as probability calibration, changing class prevalence, and monitoring minority-class recall and precision.
