Fragen aus Vorstellungsgesprächen für machine learning, von Bewerbern geteilt
The offline tasks was rather challenging, something I found quite enjoyable. These tasks involved applied mathematics exercises and one practical data analysis task. The different interviews were interactive and open discussions. The questions weren't the typical interview questions that one get asked frequently. One of the most interesting questions that I got asked was: What is one negative aspect of you that we should be aware of if we hire you ?
- what is a support vector machine? - what's the difference between a Support Vector Machine (SVM) and a linear classifier? - why do I encode visual data and do not feed the SVM with raw information? - what are the convolutional neural networks and how do they work? - how would I treat a picture of a person that wear zalando clothes? - how could I deal with a multiclass classification problem with 1,000,000 different classes? - how could I possibly help zalando to improve their services?
The telephone interview was reasonable was about Machine learning, Estimation theory, software engineering and C++ coding. The on-site interview was a bit biased to software engineering. There was no question about machine learning and it was solely C++11 , design patterns and white board coding. The questions like - name design patterns and show how to use one of them on the board - difference between modern c++ and the classical - what is rule of 5 etc The white board question: - given a text document write a c++ code to retrieve a text