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GAN-Generated Wine Attributes"
An ensemble machine learning model that predicts the quality class of wine (good, ok, or bad) based on 12 measured physicochemical properties.
Explore the world of Portuguese red wines with our interactive dashboard!
Research backed wine recommendations
CorkCrafters: Redefining the art of science and wine, one cork at a time.
Exploring, analyzing, and applying Machine learning models on the red wine quality dataset.
Why does wine taste exceptionally good sometimes, or poor? By analyzing a dataset on qualities of red wine, our team delved deep into the factors that distinguish a delightful glass of wine.
This project dives into predicting the quality of a wine using some input variables.
Predicting wine quality and pairing grape type with food.
Using machine learning to find a connection between physiochemical properties of red wine and the ratings given by human judges.
Enhancing Wine Analysis with an AI-Powered Simulator.
WineScape is a revolutionary platform that combines interactive learning with cutting-edge AI technology to offer unique experiences, crafting personalized wine blend with instant quality predictions.
Our application aims to simplify the challenges faced by amateur winemakers in crafting exceptional red wine from home through a simplifed visualization of features that affect wine quality.
We notice that when the dataset is small, traditional statistical models like logistic regression might not work well, so we want to use GAN to generate data for better results.
Our goal was to use data science models to analyze the relationship between the different chemical properties of red wine, specifically the alcohol content (ABV), density, pH, and quality.
Analysis of certain chemical variables in wines and their relation with wine quality rating.
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