Frances is the editor of ACCU’s Overload magazine. She has published articles and given talks centered on technology and machine learning. With a PhD in data mining, she has been programming professionally since the 1990s. During her career as a programmer, she has championed unit testing, mentored newer developers, deleted quite a bit of code and fixed a variety of bugs.
Many applications in variety of areas from finance to epidemiology use Monte Carlo simulations of stochastic models. This talk will cover the basics of Monte Carlo models, 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. Programming one's way out of a paper bag gives a concrete, if frivolous, application to otherwise potentially abstract concepts.
This talk will show animations in C++ using SFML and avoid too much detailed mathematics. It will build up from a very simple model, considering possible extensions to more complicated approaches on the way. People with a deep background in Monte Carlo simulations, e.g. in low discrepancy numbers, may be bored. The aim is to give a simple introduction to the topic. A brief mention of
std::random will be made.