Wine Ratings Prediction using Vivino.com database
Machine Learning And Intelligent Systems Project
The project aims to predict the ratings of French red wine thanks to machine learning and web-scraped data from the website Vivino.com.
The main goal is to help customers to find the best bottle for them according to some of their own criteria. We assume that one possible goal for the readers of the project is also to understand what really drives the ratings of wine on Vivino.com.
It could also help the wine-growers to know how a wine newly commercialized would be potentially welcomed by customers.
We first accessed the website’s database using the API requests and built a structured JSON file.
We then trained and improved machine learning models (LR, SVM & XGBoost) to predict wines’ ratings using their respective chemical properties (acidity, tannin, intensity & sweetness) and prices.
