Basic probability/statistics questions, simulation and coding
Applied Scientist Interview Questions
1,159 applied scientist interview questions shared by candidates
ML round - asked questions about overfitting, model design, precision, recall, F1 scores Coding round - design algorithm to implement byte pair encoding
Major questions were related to my project which was computer vision/DL based. 1. What are the difficulties I faced in my project and how I counteracted it? 2. Explain U-Net and what novel thing it offers? 3. Explain regularization and it's different types? 4. How KL divergence loss is different from cross entropy loss?
They asked a lot of behavioral questions. Regarding the technical questions, they asked computer vision (6 DoF pose estimation methods, YOLO, image segmentation), statistics (covariance, p-value, distributions), classic machine learning algorithms (SVM, clustering, linear regression), deep learning, regularization methods. The coding question a typical leetcode question (easy level).
Explain Dropout, how it works and why?
Tell me about network you used. Why did you choose them ?
Signed NDA. Unable to disclose
How would design a system for xxx (e.g. ASR, dialogue, object recognition) from scratch ?
The first interviewer spend maximum time on random forest algorithm and went into great detail. from bagging and boosting to gradient boosting techniques. He also spent quite some time with multiple linear regression problems. In the end there was one algorithm question. The second interviewer asked about classification for imbalanced data sets and response rate of models. In the end there were few SQL questions. Both interviewers were super helpful and walked through their questions. From my experience i think they really want the candidate to succeed.
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