Your question is Regression With Different Label Ranges. 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 would you implement two regression tasks with differing label ranges?
Assume you receive one feature matrix and two continuous targets. Explain whether you would use independent models, a shared multi-output model, or a shared model with task-specific output heads. Address target scaling, preprocessing, loss weighting, validation, and evaluation.
Provide production-quality Python code that trains both tasks without allowing the larger-scale target to dominate optimization. Report task-specific metrics and explain how predictions are transformed back to their original units.