Overview
Re-implemented and extended Geronimo Wolf’s research by web scraping wine descriptions and geographic data, then applied TF-IDF and DBSCAN clustering—tuning hyperparameters for sommelier-level recommendation accuracy.
Features
- Data Enrichment: Scrapes terroir features like soil & climate
- TF-IDF Analysis: Converts descriptions into feature vectors
- DBSCAN Clustering: Groups similar wines by geographic & flavor profiles
Built With
- Python & scikit-learn
- BeautifulSoup for web scraping
- pandas & NumPy