How do you regularize NN, explain normalization in transformers, how does BoW work, explain word2vec?
Applied Scientist Interview Questions
1,159 applied scientist interview questions shared by candidates
quali tecniche di machine learning conosci
Code a weighted distribution function so that it returns selection w probability according to weights. Similar to one on leetcode
what is the difference between rnn and lstm. answer by me lstm has a extra forget Gate to implement rnn can't remember long context and theoritically lstms can remember all the relevant history even if it's very far away. he said it's a vauge reply then interview asked about demnishing gradients which I explained , and he asked lstm vs rnn which one handle the dimnishing gragient problem better. for which I replied lstm to which he said you should have told this in lstm vs rnn at this point I was really disappointed with his knowledge , tone and attitude . but what to do he was the interviewer
There were two rounds. The first round involved basic questions to evaluate my demeanor and how I would negotiate difficult situations. The second round was a bit more technical. It involved an algorithm design question.
something like regression and BFS.
Missed several question in NLP as the position has no requirement on that. Suggest others to prepare everything, not just item mentioned in the JD.
Lots of questions revolving around Amazon Leadership Principles
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).
Previous projects related questions, ML and Statistics, some behavioral, and no coding. How do you account for error propagation in time-series forcasting?
Viewing 241 - 250 interview questions