1. Estimate the probability of a disease in a particular city given that the probability of the disease on a national level is low.
  2. How will inspect missing data and when are they important for your analysis?
  3. How will you decide whether a customer will buy a product today or not given the income of the customer, location where the customer lives, profession and gender? Define a machine learning algorithm for this.
  4. From a long sorted list and a short 4 element sorted list, which algorithm will you use to search the long sorted list for 4 elements.
  5. How can you compare a neural network that has one layer, one input and output to a logistic regression model?
  6. How do you treat colinearity?
  7. How will you deal with unbalanced data where the ratio of negative and positive is huge?
  8. What is the difference between -
    • Stack and Queue
    • Linkedin and Array

TOP MNC DATA SCIENCE INTERVIEW QUESTIONS