Mathematics for AI — Ch.06: Numerical Methods [KR]
STATERA Library · Volume 05 · Chapter 06 · KR Source: https://github.com/Statera-Library/01_Vol_05_Mathematics_for_AI/blob/main/Chapter_06_Numerical_Methods/Chapter_06_Numerical_Methods_KR.md Volume 05. Mathematics for AI 06. Numerical Methods 06.00 Numerical Computation 수치 계산(Numerical Computation)은 현대 과학 컴퓨팅(Scientific Computing)과 인공지능(Artificial Intelligence)의 기초로서, 디지털 컴퓨터(Digital Computer)를…
Numerical computation, a fundamental aspect of modern scientific computing and artificial intelligence, provides systematic methods for approximating mathematical solutions using digital computers. Unlike symbolic mathematics, which deals with exact symbolic manipulation, numerical computation operates with finite precision, representing quantities as discrete values and executing algorithms through arithmetic operations.
The primary goals of numerical computation include controlling computational cost, memory usage, and numerical uncertainty while obtaining sufficiently accurate results. Due to the finite resources of digital computers, not all real numbers can be expressed precisely, necessitating discrete representation, approximation, and carefully designed algorithms.
Understanding the limitations of numerical computation is crucial for developing reliable AI models, scientific simulations, and large-scale computational systems.
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