Not really something in particular.
Learning Technology Interview Questions
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Q: Given this company, how do you believe ML could be applied to solve some issue?
How do you feel about coaching training specialists?
Previous experience, Machine learning, Deep learning, sample problem
Tell me how you solve complex problems Tell me three things you like about yourself Tell me three things you'd change about yourself Tell me how you approach diversity in the workplace Tell me how you manage differing opinions
What are the challenges in solving the speech-text problem?
First interviewer tested me on basic probability (Bayes rule etc), binary classification (saw if I knew precision/recall under a heavily unbalanced prior), and signal processing (sampling, aliasing). The coding part was to generate all ordered substrings of a given string. The 2nd interview was a basic test on probability followed by a coding problem (implement linked list, append operation, do in place reversal of list using a single walk through the list). Problems on the final interview were coding problems and basic number theory (implement binary search, implement FIR convolution, estimate frequency of a sine wave signal based on zero crossings, implement divisibility tests for various primes).
Tell me about yourself. What do you think you can bring to this role?
How much do you know about deep learning?
1. x and y are lists. If x = y and y has been changed, what happens to x? 2. Explain ROS topic latch 3. Explain ROS queue size and how the various data types affect it 4. What are the containers in std standard library and name a few 5. Explain virtual functions in C++ 6. Struct vs Class in C++ 7. Reference vs pointers 8. What's the difference between NumPy max and argmax? 9. Explain multithreading in python and what are its disadvantages compared to C++ 10. Difference between SGD and Adam optimizer. Where do you use them? How does the learning rate work with each? 11. Overfitting vs underfitting in ML 12. Explain batch normalization 13. Difference between shared pointer and unique pointer 14. Techniques to mitigate the overfitting and underfitting 15. Dropout 16. Resnet 17. Difference between different loss function and where do you use them 18. Explain normalization 19. Explain what is public, private , protected in C++
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