If you obtained a degree in Computer Science and specialized in Machine Learning are you suppose to be able to answer these questions? What job specialization is this aimed for? Almost strikes me more as a statistical based interview.
now take a statistics major, every class is relevant, and you can still take machine learning in your electives. win win.
I came to this conclusion after I noticed more of my classmates in the mba program (wharton) as data scientists than people in computer science who took machine learning. in fact, _all_ of the CIS majors in machine learning who really wanted to be a data scientist ended up as engineers.
so then I started doing a small search on linkedin, only looking at the big tech company data scientists. selection biases aside, out of 12 profiles: 5 statistics majors, 5 business, 1 biophysics, 1 IT major.
I have also done some looking into interview questions via glass door, and you get grilled on statistics questions. this matches my one interview with uber in 2016. I only got asked 2 ML questions: what is random about a random forest, and in KNN, what happens to bias & variance as K goes to 1
if you want to be a data scientist, you need to learn stats really well or getting past the interview process is going to be very difficult.
One of the big pushes in Bayesian statistics recently has been to try to figure what the hell all these neural nets are actually doing. It's certainly not the case that the stats have been in the driving seat there.
Modern ML is applied, layered statistics.
season to taste.
A lot of these CS professors are themselves maths grads.