Monte Carlo
Monte Carlo on Beyond Market Intelligence: a running collection of 2 stories we have gathered and hand-picked because they are worth your time. Every post here touches on monte carlo in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around monte carlo, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
I ran 1 trillion Kentucky Derby simulations on a 1,000-vCPU cluster. Here’s what the model likes
I conducted an extensive analysis of the Kentucky Derby, running one trillion simulations on a 1,000-vCPU cloud cluster. This model, built using a combination of historical data and machine learning techniques, offers insights into race dynamics and potential outcomes. With the top pick, *Further Ado*, showing a significant win probability of 27.9%, this approach highlights the power of data-driven decision-making in horse racing. While not a guarantee of success, these findings provide a fresh perspective for enthusiasts and bettors alike.
Monte Carlo simulation of a sample size that used Monte Carlo
Hello everyone, I'm looking to create 1,000 simulations using Monte Carlo methods for a sample size of 200 KPIs. While I can easily generate sample populations of varying sizes, I’m facing challenges with calculating the average, minimum, and maximum of a sub-population across a set number of recursions. I believe there might be a straightforward approach to achieve this without resorting to complicated coding or calculations that would slow down Excel. Any insights or advice would be greatly appreciated! Thank you, Mike