Introduce yourself. Why do you want to join Amazon? What do you know about your profile? Then she explains more to me about my profile. Why you want to join ML Data Associate? What are your hobbies? Do you want to ask something?
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What was a challenge that I faced during my academic journey and how did I overcome it?
Some questions that were asked: - Can you perform linear regression when two features are identical? - How would you train a logistic regression model when you have many more 0’s than 1’s in your training set? - What are problems with drop-out regularization and how are they tackled? - Why does L2 regularization work better than L1 regularization? - What are random forests? The interview ended with a programming challenge on a (virtual) whiteboard. It was a hard challenge that I could not solve within the ca. 10 minutes that I was given. Having two people watch what you type of course doesn't help.
Please tell me about yourself.
Tell me about a time you would have chosen one model over the other.
HR screen was simple asking me to walk through my resume. The coding challenge was difficult but, not too much. Ford does not allow any coding language besides Python. However, the grading of the coding challenge is a problem area. I answered all 3 questions and provided the data plots and accuracy metrics in the code. But to my dismay, I discovered later that they graded me a 7% score. This was beyond belief. The recruiter refused to even cross-check if there was any s/w glitch or, human error in the exchange of files or, if there could be any problem with the HackerRank s/w itself. I was declared to be a duffer and written off. I would never interview with Ford again.
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