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I've come to the conclusion that my brain's "algorithm"y, rather than "equation"y. My scores on (especially) spatial reasoning tests are excellent so one would think I'd have a leg up in mathematics, but trying to read typical "mathy" (equation-heavy) writing makes me feel the way I assume dyslexics do, even when it's something I'm pretty familiar with.

Algorithms, though? No problem. Programming in typical Algol-family languages & similar came easily to me. The "tough" early topics? Pointers, recursion? Not even a bump in the road, totally natural. To this day, though, the ones that look more like mathematical writing (Haskell) are really hard to read, let alone write. I can get all the concepts at play in a piece of Haskell and still not be able to keep the syntax or meaning of the code itself straight. When I do want or have to read mathematics of any complexity whatsoever, I only make headway by converting it to something more algorithmic as I go ("OK, so what does this term or whatever do to any other values passing through, here?")



You're not alone. The Math symbols are easy once you learn them (at least the subset I know), but it was challenging getting there.

My field has a lot of dense math that makes the pyramids look simple (ok I exaggerate, but there is a lot going on). The only way I've been able to really grok it is by writing software to do it. Now that I know what's going on, the math notation is useful in that it explains the problem in a succint way. I think Calculus via Python with nothing but the stdlib and Matplotlib would be a better way for me to learn to be honest.




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