DBTB INT Marek Kolodziej r
summary
Argues that current datasets are good enough to build real products but CPU cycles are wasted when people run linear algebra naively, so using efficient linear algebra algorithms often beats buying fancier hardware; shows how algorithmic insights spawn new matrix routines when standard libraries lack them. Notes the open-source era and lists practical learning paths — Coursera, Udacity, Udemy, YouTube — and mentions Galvanize 12-week program as a viable jumpstart.
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