When I was moving into my ML career after years in academia, I made a pragmatic decision to just focus on getting things to work, instead of learning any theory. I thought one day I might come back to fill in the gap, but at some point I realized that it was in fact largely a waste of time.
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You aren't bad at machine learning math. You were taught by academics who prioritized dense notation over spatial intuition.
Traditional math education forces you to memorize symbols before you understand concepts.
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