Wine Quality Prediction

• Tech Stack:
• Language: Python
• Packages: Skcit-learn,Pandas,Flask
• Github URL: Project Link
• Video Demonstration: Link

In this project, I developed a machine learning model using Scikit-learn to predict wine quality based on physicochemical features like acidity, pH, and alcohol content, achieving an accuracy of 81%. I preprocessed the data by handling missing values and normalizing features, then employed various algorithms including Random Forest, SVM, and Logistic Regression, selecting the best performer through 5-fold cross-validation. The final model, a Random Forest Classifier, was deployed as a Flask API for real-time quality predictions.