What did you do in your previous job? What tools did you use? Did you process large datasets? Do you write code and how do you ensure clean code practices? What are your MLOps capabilities? What problems did your solutions have in your previous work and how did you fix them? They also asked classic ML questions: When is classical machine learning better than deep neural networks? What is boosting, bagging, XGBoost, random forest, and decision trees in general?
how to get bell curve from binomial distribution
Entrevista em grupo: Quais são meus hobbies? Discussão de case sobre dados. Entrevista individual: Perguntas sobre monitoria na faculdade Perguntas sobre experiência profissional anterior
What is your salary expectation?
Viele Fragen zu vergangenen Projekten, aber keine klassischen HR Fragen.
Explain transformer. Code gradient descent.
What is gradient descent and how does it work?
Expected value problems, sorting problems.
ML basic concepts. And a live coding problem about array.
what are SFT and RFT
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