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"Coding your way out of a paper bag"

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Many of us have heard programmers complain “They couldn’t even program their way out of a paper bag,”

Few have wondered what that might actually mean. Frances Buontempo asked herself exactly that question a few years ago. Since then she has given a couple of talks at the ACCU conference and written articles for their Overload magazine demonstrating ways in which it is possible to program your way out of a paper bag, often using machine learning.

This talk will revise the basics of Monte Carlo models (which are used in a variety of areas from areas from finance to epidemiology) and consider when they are appropriate. In particular, it will demonstrate standard and geometric Brownian motion, showing various approaches to diffusing one’s way out of a paper bag.

Though a bit frivolous sounding, programming one’s way out of a paper bag gives a concrete application to these otherwise potentially abstract concepts.

This talk is part of the Computer Laboratory Tech Talks series.

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