Your question is Designing ML Experiments. 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 did you design your experiments, what challenges did you encounter during the experiment process, and how did you address them?
Describe a practical supervised learning experiment from dataset preparation through final evaluation. Explain your split strategy, baseline, candidate models, metrics, hyperparameter search, reproducibility controls, and how you handled issues such as leakage, imbalance, missing values, overfitting, noisy labels, or unstable results. Include working Python code that demonstrates the experimental workflow and explain how you would decide whether the final model is ready for further validation or deployment.