Your question is Hyperparameter Tuning for ML Models. 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).
You're comparing several supervised learning models and want a disciplined way to improve performance without overfitting to a validation split.
How do you tune hyperparameters for a machine learning model?