5 data science questions you should be able to answer for a data scientist role.

𝐌𝐞𝐝𝐢𝐮𝐦 𝐥𝐞𝐯𝐞𝐥

1. Name ML algorithms that do not use Gradient Descent for optimization.

2. Explain how you construct an ROC-AUC curve.

3. Give examples of business cases where precision is more important than recall, and vice versa.

4. What’s the difference between bagging and boosting, and when would you use one over the other?

5. How do MLE and MAP differ?