How code slows as data grows

Wednesday 18 October 2017

One of the parts of the vacation talk I did in September at Boston Python was about big-O notation. I've noticed that topic seems to be some kind of dividing line for people who feel insecure about not having a computer science degree. I wanted to explain it in simple practical terms so that people could understand it well enough to inform their choices during everyday coding.

I liked how it came out, so I wrote it up as a standalone piece: Big-O: how code slows as data grows.

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