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 ============================ 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. ============================= 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 -- You received this message because you are subscribed to the Google Groups "massfire" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/massfire/CAFXWwKaCNX2B8mDFQd%2B%3D7kaoqG2EoUC9%2B6rhtK1kD6bwhugMgQ%40mail.gmail.com.
