Your question is Overfitting in Supervised Learning. 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 training supervised learning models and notice that training performance keeps improving while validation performance stalls or drops.
How do you approach the problem of overfitting in machine learning?