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by gwmnxnp_516a
1754 days ago
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It depends pretty much on your field. If your field is related to games, formulas related to quaternions, linear algebra and coordinates will be useful; if your field is related to data science or machine learning, then, statistics, linear algebra, tensors and optimization will be useful as well. Obviously some types of programming requires more math than others, a robotic-related programming certainly will require far more math than a vanilla crud application. |
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Beyond practical uses, I'd say calculus is essential for having a robust understanding of rates of change in different contexts. I remember when my thesis supervisor gave me an intro to three-dimensional fluid flow so elegantly with calculus, then worked statistical mechanics into the equation without compromising its structure or elegance. All the snobbery in the world around mathematics being beautiful made sense in that moment.
Since then I've completely lost my ability to explain the del operator. I'd probably fuck up a lot of working techniques solving calculus problems (integration by parts with trig, etc). But the intuition for quantities changing and moving in different dimensions, and often in higher orders, sometimes randomly, has been immensely useful for understanding abstract systems and the world around me. Great carryover to grok office politics, the flow of football plays, networked systems, power transfer in biomechanics, etc.
Unfortunately it's a real pain in the ass to explain the intuition, so it tends to serve primarily as foundational knowledge. The key is though, the foundation is rock solid.