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23 lessons
Data Tools · Module 1Module material

NumPy interview questions

22 questions interviewers ask on this module’s topics, from first principles to the follow-ups. Each comes with a model answer.

  1. What distinguishes a numeric NumPy array from a Python list?
  2. Is NumPy always faster?
  3. What do shape, ndim and size report?
  4. What does dtype control?
  5. What must be true before reshape?
  6. Does reshape always avoid a copy?
  7. How do basic slicing and fancy indexing differ?
  8. What does a boolean mask do?
  9. Why does and fail between two array comparisons?
  10. What is broadcasting?
  11. Can broadcasting produce a valid but wrong result?
  12. What does axis=0 mean for the revenue grid?
  13. Why use keepdims=True?
  14. What does argmax return?
  15. How does nan affect mean?
  16. How do * and @ differ?
  17. What does .T do to a one-dimensional array?
  18. Why solve a linear system instead of explicitly inverting?
  19. What if feature columns are linearly dependent?
  20. What does a seed guarantee?
  21. Why is one permutation used for features and labels?
  22. How do you compare floating-point arrays?

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