I was asked about my research directions in my post grad studies.
Applied Scientist Interview Questions
1,160 applied scientist interview questions shared by candidates
Zig-zag traversal of tree, time and space complexity. What is better to use tree of graph in such case. Difference between BERT and LSTM and which will be faster
ML basic questions include evaluation metrics, data processing/augmentation related, etc
questions focused on practical machine learning skills. Topics include experience with LightGBM, neural networks, and handling large datasets. Advanced techniques like word embeddings and model evaluation methods, such as overfitting prevention and hyperparameter tuning, are discussed.
What is Heteroscedasticity and how would you model it?
2 rounds of interviews: one ML theory an one code. The ML was Basic theory questions (e.g. advantage of using Relu, explain Bert). The coding was an easy problem ( remove all numbers equal to a given value from an Array, in linear time, in place)
Can you walk me through the process of building a machine learning model?
Given a generator of unbiased bernoulli numbers (0 or 1 with p=0.5), create a biased bernoulli trial generator (generate 0 or 1 with the specified 0 < p < 1)
Beschreiben Sie worum es in Ihrer Doktorarbeit ging?
There was a 1- a review of my past experience 2- the description of a difficult applied problem I was involved in 3- case study 4- a coding question (find the two highest numbers in a sequence)
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