In this project, I utilized Kaggle's Red Wine Quality dataset to develop several classification models aimed at determining whether a specific red wine can be classified as "good quality" or not. The dataset originally assigns a "quality" score ranging from 0 to 8 to each wine. For the scope of this project, I transformed the output into a binary classification, categorizing each wine as either "good quality" (with a score of 7 or higher) or "not good quality" (with a score below 7). The primary focus of this project was on employing the Random Forest Algorithm to construct the predictive model.
https://www.kaggle.com/datasets/uciml/red-wine-quality-cortez-et-al-2009?select=winequality-red.csv