Fragen im Bewerbungsgespräch: Machine learning | Glassdoor.de

Fragen im Vorstellungsgespräch: Machine learning

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Fragen aus Vorstellungsgesprächen für machine learning, von Bewerbern geteilt

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Implement a CNN classifier in Keras syntax and NO dataset was given.

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I was a bit surprised by this, as NO dataset is given and such a large task is asked over a phone. I tried to form my approach that I would first try basic classifier and they explain him about how CNN can be formed.

What do you know about Convolutional Neural Networks?

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The task was to rank the sensors according to their importance/predictive power with respect to the class labels of the samples

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Python program to draw line

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To rank the sensors according to their importance/predictive power with respect to the class labels of the samples (on Python)

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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 ?

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- 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?

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Build a machine learning model to map the measurement of three accelerometer time series data with a time series data of an optical sensor

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

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