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400Volts OP t1_j4h5ne2 wrote

Not yet, I'm trying to gather as much information as possible to make the best move career-wise

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junetwentyfirst2020 t1_j4h8p07 wrote

If you want a job with the title research in it, then you are 99% going to need top tier conference publications in your masters. Even one ICCV, ECCV, CVPR should be enough, but they are very competitive. I wish I knew that a masters was different from an undergrad because I was completely unready.

I’d suggest reading some research papers to gauge your math, especially. All of Computer Science for ML/DL is basically applied math contributions. Look up the papers noted in the course CS231N and if you can’t get through them, then you need to improve your math skills. I wish someone told me this before my masters because my math sucked and it held me back significantly, and it’s hard to try to both do a masters and then play catch up on math because the masters itself is a lot of work.

I have an undergrad and masters in CS, thesis on DL, and 3.5 years industry experience as a Machine Learning/Computer Vision Engineer and I don’t even both applying for jobs that say Research in the title because everyone in the world with a pub is applying for those same jobs.

You can do it if your math is solid (linear algebra, calculus, and probability), knowing how to code is needed but not the most needed thing and you can tell my the horrible research code out there, so don’t rely solely on your software engineering skills.

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blacksnowboader t1_j4hpx5o wrote

Quick question, what is CS231N? And where is that course taken?

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junetwentyfirst2020 t1_j4hqfvl wrote

Stanford university course taught by Andrew Karpathy. It’s a little older now but I do think it covers important material. You can find it on YouTube

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