[cyber_kinetist]

You still need to understand some basic theory/math about probabilistic inference (along with some knowledge of linear algebra), or else you’ll get a bit overwhelmed by some of the equations and not understand what the papers are talking about. PRML by Bishop is probably more than enough to start reading ML papers comfortably though. (This would probably be too easy for a competent math major, but not all of us are trained that way from the beginning…)

[jeffreyrogers]

I'm not sure why you're getting downvoted. I find it hard to believe that someone without a decently strong math background could make sense of a modern paper on deep learning. I have a math minor from a good school and had to brush up on some topics before papers started making sense to me.