First being the introductory call exploring the previous work and depth in it. Second round was a case study , a ML problem statement was given and a holistic solution considering data, architecture, latency monitoring was expected. Third round was paper discussion, A published research paper is shared prior to the interview. During the interview, the paper is discussed and critiqued, questions were asked around paper's novelty, short-comings, performance at different metrics, its usability/reproducibility and how the work can be continued further.
Machine Learning Interviews
Machine Learning Interview Questions
"To get a job in machine learning, you must have the programming and mathematical knowledge to create artificial intelligence that is capable of learning new tasks without being explicitly coded. In an interview you may be asked about your experience with pertinent coding languages such as Java and C++ as well as with writing algorithms. The interview will be comprised mainly of technical questions that test your knowledge of the fundamental concepts of machine learning such as data mining and signal processing."
8,221 machine learning interview questions shared by candidates
Common ML questions such as overfitting, unbalanced data set, supervised and unsupervised, etc.
They asked about classical machine learning then the field that you continued your study in.
More statistical questions and presentation
The phone screen has LC tagged Bloomberg question
Tell me somthing about your self?
Regarding ML, DS and other AI and python related.
Given two sorted arrays nums1 and nums2 of size m and n respectively, return the median of the two sorted arrays. The overall run time complexity should be O(log (m+n)).
Can you explain a linear SVM?
Back-propagation; the bias-variance tradeoff, the precision-recall tradeoff
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