Practice for the Rakuten interview with these recently asked interview questions.
| Question | Topic | Difficulty |
|---|---|---|
Machine Learning | Hard | |
Assume you have a logistic model that is heavily weighted on one variable and that one variable has sample data like 50.00, 100.00, 40.00, etc…. Next let’s assume that there was a data quality issue with that variable and an unknown number of values removed the decimal point. For example 100.00 turned into 10000. Would the model still be valid? Why or why not? How would you fix the model? | ||
Statistics | Easy | |
Probability | Medium | |
SQL | Easy | |
Machine Learning | Medium | |
Statistics | Medium | |
SQL | Hard | |
Machine Learning | Medium | |
Python | Easy | |
Deep Learning | Hard | |
SQL | Medium | |
Statistics | Easy | |
Machine Learning | Hard |
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Most data science positions fall under different position titles depending on the actual role.
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