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I am in academia, but some of my students have returned somewhat disgruntled from their internships in companies claiming to do machine learning, while in pract
by danieldk 9y ago
I am in academia, but some of my students have returned somewhat disgruntled from their internships in companies claiming to do machine learning, while in practice their systems were primarily rule-based and the work consisted of writing rules [1].
I now recommend students to find out whether companies are just name dropping ML or doing serious ML work. Typically, the best way is to ask former employees/interns. But I question directed at this also would not hurt.
[1] There is nothing wrong with that, but it sets the wrong expectations.
- nl 9y agoI work in industry (sort of) and this is very true. One of the reasons for this is that the people designing the systems don't know how to do anything else. There's such a huge, huge gap between using ML to do the same thing everyone else is doing (say... image classification, or maybe regression on volume vs sales...) and solving unique business problems using ML.