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Data Intern Interview Questions
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Technical: Given data on taxi drives (pickup time, date, etc), create a dataframe with specific features.
What achievement you get in your best project?
1) What is the difference between hyperparameter and parameter? 2) What is a gradient boosting algorithm? 3) What are the assumptions of linear regression? How would you check the assumptions? 4) Why should errors be minimized? 5) How would you check multicollinearity? 6) What is VIF? 7) What is TF-IDF? Why is logarithm used in it? 8) What is SMOTE? 9) What is overfitting? How would you prevent it
Tell me about a time you solved a problem?
Tell me about yourself. What did you do in XXX project
What is ur weakness in group project
Tell me about yourself, why did you apply
Describe yourself what did you do when you face conflicts in your team?
Show you would implement a tree and DFS on that tree.
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