math for ai - a book available online via bpl

[Peteri Szerlagi]

this paragraph is from the 3rd chapter of the book at the point where
the first mathematical formula appears - we are immediately lost -
what is a 'dependancy'?

oh well

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Linear dependencies model flatness in the world, like one-dimensional
straight lines, two-dimensional flat surfaces (called planes), and
higher-dimensional hyperplanes. The graph of a linear function, which
models a linear dependency, is forever flat and does not bend. Every
time you see a flat object, like a table, a rod, a ceiling, or a bunch
of data points huddled together around a straight line or a flat
surface, know that their representative function is linear. Anything
that isn’t flat is nonlinear, so functions whose graphs bend are
nonlinear, and data points that congregate around bending curves or
surfaces are generated by nonlinear functions.

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this is from the OReilley system -
https://learning-oreilly-com.ezproxy.bpl.org/library/view/essential-math-for/9781098107628/ch02.html#idm44895117828368
- essential math for AI is the book

its free to use and read if you have a bpl card

--
shes got a kid ... together -
https://youtu.be/IQQ-hxIwm70?si=8jrwZRcfZg-vN4Ye&t=237