> For the complete documentation index, see [llms.txt](https://stephanosterburg.gitbook.io/scrapbook/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://stephanosterburg.gitbook.io/scrapbook/math/math-for-ml/linear-algebra/wk1.md).

# Wk1

## Mathematics for Machine Learning: Linear Algebra

Basic Example: *multiply a matrix by a vector*

$$
2a + 3b = 8 \newline
10a + 1b = 13 \newline

\left (\begin{matrix}
2 & 3 \ 10 & 1
\end{matrix} \right)
\left \[\begin{matrix}
a \ b
\end{matrix} \right]
====================

\left \[\begin{matrix}
8 \ 13
\end{matrix} \right]
$$

The order in which we add vectors doesn't matter, called Associative ->

$$
(r + s) + t\newline
r + (s + t)
$$