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My model performs badly. Is my project ruined?

No, and a careful analysis of why usually scores well. Diagnose whether it is underfitting, overfitting, insufficient data or an unlearnable problem, show the evidence, and say what you would try next. Reports that quietly present a weak model as a success are the worse outcome.

This comes up on Machine Learning Coursework, where it is answered in the context of the work itself.

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