What is the time complexity of this solution? What is the space complexity?
Machine Learning Researcher Interview Questions
1,879 machine learning researcher interview questions shared by candidates
Diagram the architecture of a software system you are familiar with. Follow up questions relate to reliability, monitoring, fault tolerance, etc.
2 leetcode questions. 1 easy and 1 hard
Explain the guts of Shor's quantum factoring algorithm. (this sort of came up naturally, so we figured we'd discuss it together)
Finding the output dimension of a convolution process, given the input size, kernel size, and stride.
A MLOPS app expecting automation at every step possible
Like i said they asked about different topics.
They asked about java and C++.
1. Give your introduction. 2. Questions about MS Project- Image Processing, what you do in that project and what were your findings. 3. One question about, explaining the Ph.D. research work in short. 4. What kind of models are used in research, regression, or classification? 5. What was the input/output dataset for your model? 6. What preprocessing technique did you apply to your data? 7. What is R2 score and why do we use it? 8. What is adjusted R2 score? 9. What is bias and variance? 10. What is overfitting and underfitting, explain them. 11. Techniques to overcome them. 12. Why you used RFR in your data, explain its working, what is bagging and boosting? 13. What technique is used to determine the best hyperparameters? 14. What is cross validation and why it is used? 15. What is feature engineering? 16. One question about CNN project work, what layers I used and why? 17. Which activation function is used in the output layer of CNN classification problem? 18. Difference between Object classification and segmentation. 19. How can we convert spatial coordinates to image?
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