Learn Linear Algebra and Vector Spaces to See Neural Networks as High-Dimensional Geometry
TivadarDanka · x · 2026-10-09
Tivadar Danka argues that anyone serious about AI should learn the math deeply: see matrices as spatial transformations, calculus as the language of optimization, and master vector spaces—until neural networks stop looking like black magic and start looking like high-dimensional geometry. Deep mathematical understanding, he says, is what separates an API-wrapper developer from an AI architect.
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