Joe recently teamed up with IBM and Aginity to create a proof of concept "Moneyball" app for the IBM Think conference in Vegas. The original goal was to prove that different tools (e.g. H2O, Aginity AMP, IBM Data Science Experience, R and Shiny) could work together seamlessly for common business use-cases. Little did Joe know, the app would be used by Ari Kaplan (the real "Moneyball" guy) to validate the future performance of some baseball players. Ari recommended one player to a Major League Baseball team. The player was signed the next day with a multimillion-dollar contract. This talk is about Joe's journey to a real "Moneyball" application.
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Making Multimillion-Dollar Baseball Decisions
Jo-fai (Joe) was a civil engineering professional by trade. He used to build simple models with spreadsheets and MATLAB. A few years ago, he decided to participate in one of the very first MOOC (Intro to AI) where he met a group of data geeks and found a rather addictive site called Kaggle. From there he discovered the wonderful world of data science as well as some amazing open-source tools. The skills he learned from Kaggle competitions effectively led to many opportunities outside his domain. After leaving the civil engineering industry, he worked for Domino Data Lab and Virgin Media as a data scientist. He joined H2O.ai a few months ago.