Hey Ryan, I see this question asked very often in the last year or two. I am not an expert on deep learning, nor have I taken the deeplearning.ai track, but am

Hey Ryan, I see this question asked very often in the last year or two. I am not an expert on deep learning, nor have I taken the deeplearning.ai track, but am currently learning about the topic. Some of the resources out there have nice primers. I think you need to be somewhat comfortable with understanding the usual log/exp functions for the very base, understand calculus, with partial derivatives, and be used to linear algebra and matrix operations. Some good understanding of statistics could be useful as well when learning about ML. I don't think that a good background in CS is necessary for this stuff. This has not much to do with programming languages, operating systems, Turing completeness. Maybe having a good base in algorithms could be useful for _implementing_ the libraries to make sure they are optimal. I was wondering why do people ask this question (or ask about resources on learning about this topic in general), when answers on this are so easily findable online.