1. How do you handle missing or corrupted data in a dataset?
  2. Do you have experience with Spark or big data tools for machine learning?
  3. Pick an algorithm. Write the psuedo-code for a parallel implementation.
  4. What are some differences between a linked list and an array?
  5. Describe a hash table.
  6. Which data visualization libraries do you use? What are your thoughts on the best data visualization tools?
  7. How can we use your machine learning skills to generate revenue?
  8. What do you think of our current data process?
  9. What are the last machine learning papers you’ve read?
  10. Do you have research experience in machine learning?
  11. What are your favorite use cases of machine learning models?
  12. How would you approach the “Netflix Prize” competition?
  13. How do you think Google is training data for self-driving cars?

TOP MNC MACHINE LEARNING INTERVIEW QUESTIONS