Your question is Choosing the Right ML Algorithm. 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 are given a business problem and a labeled dataset, but the team is unsure which machine learning algorithm to use. The right choice depends on the data, the error costs, and how the model will be used.
The dataset may be tabular, sparse, time ordered, or high dimensional, and the target may be binary, multiclass, or continuous. You need to pick an algorithm that fits the problem instead of defaulting to one model family.
How do you decide which algorithm is appropriate for a given business problem?