7 ms·
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 i
by hackernewsacct 9y ago
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.
- RandomInteger4 9y agoStatistics is used heavily in machine learning.
- ju-st 9y agoI have the impression that at big universities maths is always the #1 topic in CS/ML. So its no surprise their graduates ask the same riddles as their profs.
- chronic6h2 9y agoAs long as these riddles keep the web devs and infra engineers away from machine learning, I'm all for it. We must preserve the elite reputation associated with machine learning; not watered down by avergae engineers looking for a career change.
- stale2002 9y agoPeople have been doing statistics for decades, which is mostly all that machine learning is. Coming up with a fancy new buzz word for stuff that has been for decades, doesn't make something "elite".
- chronic6h2 9y agoThen why do machine learning scientists get paid multiples more than statisticians? Why do CS departments get far more funding for ML grants than the same grant branded from the statistics department? Say what you want about ML vs statistics, the fact is: in both academia and industry, machine learning is far sexier than statistics.
- mamon 9y agoYou know, statistics is a branch of mathematics, and mathematical education itself can be considered "elite", if for no other reason then for the irrational fear it induces in most of people. Most of high school graduates decides to pursue more "practical" topics like CS, leaving mathematics to those chosen few who dared to study it :)
- gaius 9y agoCS is discrete maths, which is not quite the same as statistics.
- screye 9y agoI personally know a few ML professors at my university who are not taking any CS grads as pHDs. They only want people with maths degrees. A lot of these CS professors are themselves maths grads.
- cropsieboss 9y agoQuestions look answerable for someone taking 2 courses in machine learning. One being the introduction.
- cfusting 9y agoStatistics and machine learning have a huge amount of overlap. Almost seems silly we separate the fields.
- gaius 9y agoWell yes. Before the trendy buzzword, machine learning was known simply as predictive statistics.
- pmiller2 9y agoNo idea why this was downvoted; I find this to be an accurate description. The difference between stats and ML is mostly one of terminology and perspective. I studied math in college and grad school, and there were several moments in Andrew Ng's online lectures where I thought "oh, I know this, but we didn't call it that, and I had no idea it was considered ML."
- flamedoge 9y agoreminds me of the whole Bayesian perspective of ML
- lottin 9y agoOr simply statistical modelling. I think there are methodological differences though. To me ML seems like a massive p-value fishing operation.
- spencer_ochs 9y agoDo you mind elaborating? I can't think of any methods that explicitly (or implicitly) use p-values. The only place in the industry I have seen p-values used is AB-testing, but most seem to be trying to move to a multi-armed bandit, bayesian methodology.
- autokad 9y agoa degree in computer science is really inefficient if you want to be a data scientist. imagine a 10 class CIS masters: with graduation restrictions you might be able to take 3 classes that directly relate to data science. good luck in your job interviews if you took them first, as you spent 20 hours a week on homework to fill requirements you will never use. 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.
- white-flame 9y agoClassical AI is applied, layered logic. Modern ML is applied, layered statistics. season to taste.
- cirgue 9y agoMachine learning systems that perform a job and make money are still overwhelmingly stats-based, and the knowledge required to understand, tune, and optimize any ml system, regardless of design, are based on statistics and always will be.
- deong 9y agoI'm not sure I wholly agree there. There's an awful lot of real work being done that makes real money based on deep learning, and deep learning comes from the CS "it works, what's the problem" side of the field as opposed to the statistics "I want formally grounded theory for everything" side. 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.
- cirgue 9y agoMachine learning systems that perform a job and make money are still overwhelmingly stats-based, and the knowledge required to understand, tune, and optimize any ml system, regardless of design, are based on statistics and always will be.