This project aims to leverage machine learning techniques to identify widely acclaimed wines using market-available features, overcoming the limitations of complex, lab-based prediction methods. The core objective is to provide a predictive model that assists three key stakeholders: consumers making purchasing decisions, wine cellar owners selecting inventory to import, and winery owners understanding general public preferences.
collaborator : Kuan-wei Tseng