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Posted

Hey all, I am relatively new to this site. I won't ask you to rate my profile (although you can if you want), but I just have a few questions regarding machine learning programs. I am looking to apply to places in the northeast (Cornell, CMU, MIT, University of Amherst, Stony Brook, Columbia). I am just wondering what the advantages/differences are between the different programs. Also, some of the schools don't have a specific machine learning department; instead it would be found within the Comp. Sci. or Stats departments. I am slightly intimidated when considering applying to these schools, but I figure it makes sense to be where the cutting edge research is happening, since this is a relatively new field.

Here is my background, if anyone would like to give me some advice:

Double major in Math and Statistics at Stony Brook University (3.5 GPA)

Currently in a Masters in Statistics program at Columbia University (about the same GPA)

I don't have formal research experience, but my classes this semester have some advanced final projects.

GRE - 800 Quant, 500 Verbal, 4.5 Analytic Writing

2 good letters of recommendation from professors this semester, 1 generic from my undergraduate department chair

Posted

Very few schools have a separate machine learning department.

Your question is so vague that it's hard to answer, honestly. These programs differ in all sorts of ways - number of students, stipend level (and local cost of living), job placement rates, percentage of graduates who end up in academia, [in]formality of the culture, emphasis or lack thereof on interdisciplinary work, requirements to get the PhD, average time to completion, quality of the facilities...I could go on and on. I suggest creating your own customized ranking at phds.org.

The person who is going to have the greatest impact on your experience is your advisor. It is a mistake to look only at a bunch of top departments and say "Well, that is where the cutting-edge research is, so that's where I will apply." Cutting-edge research can happen just about everywhere - most programs have a truly outstanding faculty member or two. Look back at papers that you thought were cool, and find out where the people who wrote them are. You are going to want to apply to some non-top departments as well as the top ones, and you might as well figure out what those are.

I can tell you that if you have no research experience you have very little chance at the top programs. A lot of them (CMU, for example) use that to screen people. However, there is such a thing as a final project for a class that is also research experience (I got a conference poster presentation out of a term paper a while back). Obviously, since I don't know anything about your final projects, I can't judge them.

  • 2 weeks later...
Posted (edited)

Hi geekman,

As starmaker said, most places don't have a separate machine learning department, but have it as a subfield of Computer Science, or some even have it under Artificial Intelligence within the Computer Science department. As for the schools you listed in terms of reputation, CMU is probably the most highly regarded or machine learning, with MIT close behind. Keep in mind that those two will be very competitive - MIT got 2700 applications last year for Computer Science and gave around 100 admissions. Columbia is very good in statistics I think, while Cornell and Amherst both are highly regarded in machine learning. Stony Brook, while still well reputed, is probably less so than the others. As starmaker said though, your rankings of those schools will be determined by a lot of factors that you will have to consider.

Edited by newms

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