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I'm Software Engineer who applied to grad school for Machine Learning/Computer Vision PhD and currently waiting for interview calls. I'm brushing up Linear algebra/ ML topics. What kind of technical questions do professors generally ask in Ph.D interviews ?

Thanks in advance.

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closed as off-topic by Siong Thye Goh, Kiritee Gak, user12075, oW_, Sean Owen Jan 15 at 21:00

This question appears to be off-topic. The users who voted to close gave this specific reason:

  • "This question does not appear to be about data science, within the scope defined in the help center." – Siong Thye Goh, user12075, Sean Owen
If this question can be reworded to fit the rules in the help center, please edit the question.

  • $\begingroup$ I guess it is very needed to be familiar with the concepts in pattern recognition and statistical learning. The concepts about distributions of features. $\endgroup$ – Vaalizaadeh Jan 15 at 6:38
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In general, linear algebra and basic concepts in statistics (probability distributions, marginalization) and machine learning (you should be familiar with terns like Maximum-A-Posteriori estimation and Maximum-Likelihood-Estimation, maybe Markov chains and SVMs, neural-networks, etc.).

Best practice would be to find out who is interviewing you and than look at what courses he is leading and what papers he has published in recent years. He is most likely to ask specific question from his field of expertise and interests.

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