Brain teaser, tree-method, and machine learning specifics
Machine Learning Internship Interview Questions
8,208 machine learning internship interview questions shared by candidates
Perform exploratory data analysis on given data set, identify by outliers, handle outliers and plot them
Writing loops in Python or other languages
How would you build a model, you can decide on the data, if many additional data or only historical time series.
A search algorithm question, and a parsing and organizing question.
How to implement linear regression on python (from scratch)?
find min, max, and an average of sound note
Three coding challenges followed by video recording to explain your codes. Then competency question.
You will be asked a wide range of ML-related questions (ML theory, PyTorch, CNNs, etc.). You will also be asked to code towards the end of the 1 hour session (Leetcode medium). Most of these questions have well-defined answers (e.g., how do you disable gradient computation in PyTorch) while others are more open-ended (e.g., how would you use unlabeled data to boost the performance of your supervised tasks). My major complaints are with these open-ended questions. The interviewer had specific answers in mind and would not understand/accept alternative approaches. The depth of the interviewer's ML knowledge is also questionable as the interviewer did not understand how pretrained networks can be used as feature extractors. The interviewer also asked about variational auto-encoder without knowing the underlying probabilistic formulation. Overall, a negative experience.
Resume questions and coding round was on textual entailment.
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