The interview questions were some behavioral ones, then some fundamental questions about machine learning concepts and definition of different algorithms, how to select one method over another one considering the data. The next phase was coding interview with two questions, some tricky questions also asked.
Text methods (latent, etc), he asked if I knew anything about these.
Asked about Ito's formula as stochastic calculus is on the resume, although it's totally unrelated to the job.
Describe a time when you were committed to a job or project but had to quit.
Lots of behavioral questions, e.g., tell me about a time that you had to combined knowledge from two different areas. Technical questions included discussion on thesis topic and a design question: how to design an algorithm to effectively operate a robot in a warehouse setting.
A few questions on algorithmic complexity
Given a dataset, develop a machine learning model for classification using Jupyter notebook
Describe your typical workflow. Describe what models you commonly use.
Hyperparameters for Logistic regression Why Random forests reduce overfitting
They showed me a confusion matrix and I was asked to evaluate the performance of the model
Viewing 7961 - 7970 interview questions