Job Interview Experience For The Role Of Data Scientist - Programmatic and Digital at Procter & Gamble
1. What is the benefit of dimensionality reduction?
2. How do you select an appropriate value of k in k-means?
3. Explain bagging and boosting in Data Science. Have applied it in any of your project, if yes then which algorithm did you use?
4. What is Regularization and what kind of problems does regularization solve?
5. What is the difference between squared error and absolute error?
6. How will you explain logistic regression to an economist, physican scientist and biologist?
7. During analysis, how do you treat missing values?
8. Do you think 50 small decision trees are better than a large one? Why?
9. How will you assess the statistical significance of an insight whether it is a real insight or just by chance?
10. Explain the method to collect and analyze data to use social media to predict the weather condition.
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