Interview Guides
You're preparing a supervised learning dataset and notice suspicious extreme values, inconsistent labels, and uneven representation across groups. You want a training set that supports good generalization without hiding real signal.
How would you manage data issues such as outliers, noise, and biases in training datasets?
