Google Cloud and NCAA® have teamed up to bring you this year’s version of the Kaggle machine learning competition. Another year, another chance to anticipate the upsets, call the probabilities, and put your bracketology skills to the leaderboard test. Kagglers will join the millions of fans who attempt to forecast the outcomes of March Madness® during this year's NCAA Division I Men’s and Women’s Basketball Championships. But unlike most fans, you will pick your bracket using a combination of NCAA’s historical data and your computing power, while the ground truth unfolds on national television.
In this repo you'll find all the data along with my work throughout the Kaggle March Madness Machine Learning Challenge 2018. Most notably, check out Kaggle March Madness Challenge 2018.ipynb for my primary notebook and walkthrough of the process that I took to land in the 90th percentile.
I wrote a Medium post on the experience as well. You can find the post and more about my methodology here:
Machine Learning Madness: Predicting Every NCAA Tournament Matchup