Data Science Interviews
Sample (from 107 notes)
|Front||How does a random forest work?|
|Back||Bagging multiple decision trees.Plus "feature bagging," selecting the split feature from a random subset of all features, to reduce correlation between trees|
|Front||Significance test for binary (binomial) outcomes (e.g., conversions out of visitors)|
|Back||\(\chi^2\) with 1 d.o.f.or, for small samples or unbalanced classes, Fischer's Exact Test based on the hypergeometric distribution.|
|Front||Describe something you've enjoyed in your previous experience|
|Back||<your response here>|
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