Akash‘s 17th Data Science interview experience:
Previous round: Online Python coding test
  1. What are the assumptions of Linear regression?
  2. What is multi collinearrity? What’s the threshold you took for vif?
  3. What the formula of vif?
  4. Whats the meaning of precision and recall?
  5. Why is Xgboost better than Gradient boosting?
  6. What are different boosting algorithms?
  7. Whats the difference between boosting and bagging?
  8. If R squared is less than adj R squared will you accept the model?
  9. What exactly is the p-value in statsmodel OLS regression package?

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