数学と統計の基礎
ベクトル・行列・確率・微分 —— AI の言語
OVERVIEW
- 全項目
- 6
- 初級
- 3
- 中級
- 2
- 上級
- 1
Every model ultimately reduces to operations on vectors and matrices, and every act of “learning” is ultimately the reduction of a loss along a gradient. This domain does not aim for a mathematician’s completeness; it selects only what is needed to understand AI: linear algebra gives data and weights their shape, probability gives uncertainty its measure, and calculus gives improvement its direction.
この領域が答える問い
- Q1
Why can data be written as a matrix?
- Q2
Which direction does the gradient actually point?
- Q3
Why can softmax be used as a probability?