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Machine Learning Engineer Intern Interview Questions
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There were some algorithmic questions (basically they describe a case where you need to do a complicated search over large datasets, I solved the problem via KD-trees, which the reviewer seemed to like, but they ended up implementing a giant hash instead).
CTO Round- Situation based question about Semaphores
How to handle data with imbalanced labels in classification?
What kind of work culture would you prefer?
How did you evaluate the model?
First two sessions requested to resolve LeetCode style problem solving and I felt it's about medium difficulties. Other sessions were related to ML related topics such as attention mechanism, inference efficiency
Q1: Salary expectation Q2: Solve a scala and python problem.
Implement Deque. 50% credit if using in built library
Implement a map, include put, get, delete methods
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