Wine Quality Analysis and Prediction

Built predictive models in R to determine wine quality based on attributes like acidity, alcohol content, pH, and sugar levels. Analysed datasets to explore relationships between chemical properties and wine ratings, developing and evaluating classification models to predict quality. This project provides a data-driven approach to assessing wine quality, offering insights for optimising production and aiding both producers and consumers. Tools used include R, Data Preprocessing, and Machine Learning. Below, the images illustrate variable analysis and the importance analysis of the predictor variables.