We found this article on Interface's blog. We thought it was an awesome story about how Interface's web school turned a busy woman's career around. Despite obstacles of daily life, Miranda Tharp jump-started a web development career.
At the beginning of the project, we set out to show how the 2017 NCAA College Basketball Tournament could be a proving ground for Machine Learning analysis. There are very few places in the world where we can use the same model to predict multiple outcomes in a short period of time, have a ready-made scorecard (Vegas), have the general public understand what we are trying to do, and have a chance to "beat" the algorithm with their own knowledge.
After the first weekend of basketball, our Machine Learning Prediction tool has good results.
The Cabri Group / CAN Machine Learning Lower Seed Win Prediction tool has made its first round forecast! Without further ado:
Machine Learning and the NCAA Men’s Basketball Tournament Methodology
<<This article is meant to be the technical document following the above article. Please read the following article before continuing.>>
“The past may not be the best predictor of the future, but it is really the only tool we have”
Contemporary Analysis (CAN) and Cabri Group and have teamed up to use Machine Learning to predict the upsets for the NCAA Men’s Basketball Tournament. By demonstrating the power of ML through our results, we believe more people can give direction to their ML projects.
We are now accepting applications for the June 2017 cohort of the Omaha Data Science Academy!
Any person you hire for your team is an investment. You take careful steps to ensure their fit in the company. You go the extra mile to ensure their skills translate as perfectly as possible to the position you seek to be filled.
Investing in employees means more than just treating them well by giving them benefits and a flexible schedule. It means putting time and resources into individuals who have potential for greatness, but may need a little guidance.