The first stage was a phone interview with a research scientist, where he asked some basic machine learning questions, and details about the past experiences; what limitations did it have, and what could be done additionally to solve it.
Interview questions [1]
Question 1
Q. How can we compare two machine learning algorithms?
Q. How do we determine the complexity of an algorithm?
Q. What are the ways to reduce overfitting?
Two interviews, the first one more of an introduction and then some coding questions for robotics (FK/IK, Torch). The second one is mostly research chat, and going into the depth of my research. Both seemingly went well, except at the end of the second one, there were some Python production code questions (PEP standards, tricky pass-by-value/reference questions) that I struggled with a bit.
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