Home Depot Product Search Relevance, Winners' Interview: 2nd Place Thomas, Sean, Qingchen, & Nima

The Home Depot Product Search Relevance competition challenged Kagglers to predict the relevance of product search results. Over 2000 teams with 2553 players flexed their natural language processing skills in attempts to feature engineer a path to the top of the leaderboard. In this interview, the second place winners, Thomas (Justfor), Sean (sjv), Qingchen, and Nima, describe their approach and how diversity in features brought incremental improvements to their solution. Thomas is a pharmacist, with his PhD in Informatics and Pharmaceutical Analytics and works in Quality in the pharmaceutical industry. At Kaggle he joined earlier competitions and got the Script of the Week award.