1. Write the code to reverse a Linked list.
  2. What assumptions does linear regression machine learning algorithm make?
  3. A stranger uses a search engine to find something and you do not know anything about the person. How will you design an algorithm to determine what the stranger is looking for just after he/she types few characters in the search box?
  4. How will you fix multi-colinearity in a regression model?
  5. What data structures are available in the Pandas package in Python programming language?
  6. State some use cases where Hadoop MapReduce works well and where it does not.
  7. What is the difference between an iterator, generator and list comprehension in Python?
  8. What is the difference between a bagged model and a boosted model?
  9. What do you understand by parametric and non-parametric methods? Explain with examples.
  10. Have you used sampling? What are the various types of sampling have you worked with?
  11. Explain about cross entropy ?
  12. What are the assuptions you make for linear regression ?
  13. Differentiate between gradient boosting and random forest.
  14. What is the signigicance of log odds ?

TOP MNC DATA SCIENTIST INTERVIEW QUESTIONS