Your question is Model Optimization Techniques in Practice. 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 need to improve generalization without overfitting. You want to explain how you optimize models in a disciplined way rather than just trying random settings.
What is your experience with machine learning model optimization techniques?