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Advice Prepping for Math Subject GRE


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This posting is about the Math Subject GRE, not the Quantitative section of the regular GRE.



I applied to grad schools this season (for fall 2014 enroll) but am worried I will not get in since I didn't have a subject GRE.  I want to prep for the subject GRE now so if I do not get in anywhere I can be prepared to take the subject before re-applying.



Without going into too much detail, I want to study machine learning (ML).  Since my background is in math and statistical programming, I am applying to applied math programs that have a strong ML focus (or ML labs nearby) rather than Computer Science departments with ML. One example is Johns Hopkins dept of Applied Math and Statistics.



I have a BA in Math and Econ (2012).  I thought I wanted a Ph.D. in econ, so when I was in undergrad, I took math courses that would be most useful for an Econ program.  As a consequence, I didn't take a lot of the material that is covered on the subject GRE.  Since I have a math major, I have the ability to independently learn math materials and I can write and read proofs just fine.  I just need to know which textbooks are most important to pick up to fill in my gaps.


Classes I've Taken:


Single- and Multi- variable Calc

Differential Equations (though this course was pretty limited)

Linear Algebra

Real Analysis


Linear Optimization / Operations Research


Statistics / Econometrics


When I picked up a book on the subject GRE (Princeton Review), I noticed that it talked about geometry, algebra, and complex analysis, which I know right now I should go learn.  But it's not likely that I will be able to teach myself all these in the next 5 months (I also have a full time job), so I need to know where to prioritize.


Thanks so much!!  Let me know if you want more info...


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