Wine quality Classification
تفاصيل العمل
The Problem: Wine quality assessment traditionally relies on manual tasting and expert judgment, which can be time-consuming, subjective, and difficult to scale. Producers and businesses need a more efficient way to classify wine quality using measurable chemical characteristics. The Solution: A machine learning pipeline developed using Scikit-learn to analyze physicochemical properties of red and white wines. The workflow includes data preprocessing, outlier handling, feature transformation, scaling, class balancing with SMOTE, and Logistic Regression modeling. The model predicts whether a wine belongs to a good or poor quality category, enabling faster and more consistent quality evaluation and decision-making.
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