How To Win A Data Science Competition

Author(s): Brandon Walker

Originally published on Towards AI.

This article is about in-person data science competitions that are judged holistically, and not graded by some accuracy metric (like Kaggle). I have participated in two data science competitions (placed 4th and 1st), and I’ve mentored at Texas A&M’s first-ever datathon (3 out of the 4 teams I worked with won prizes). Consequentially, I have seen many projects, and I have noticed some trends between winners and losers. Here are my suggestions for improving your chances of winning.

Currently, I see a lot of data science projects that are just Jupyter notebooks. Unfortunately, these are frequently filled with code cells and… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI