🍷🍷🍷Red Wine Quality Prediction Model🍷🍷🍷

🍷🍇 About the Model:

• Predicts the quality of red wine based on its chemical composition.
• Built using Random Forest Classifier for accurate results.
• Features:
  • 11 input features, including alcohol, acidity, sugar content, etc.
  • Target: Quality score from 3 to 9.
• Split data into training and testing sets for evaluation.

📊 Performance:

• Achieved an impressive accuracy score of 72.5% on the test set.
• Visualized decision tree structure for better understanding.

🚀 How to Use:

1. Clone the GitHub repository:

   git clone https://github.com/username/red-wine-quality-prediction.git
   

2. Install required libraries (listed in requirements.txt).
3. Run the Jupyter Notebook (Wine-quality Model.ipynb) to train and evaluate the model.

📝 Note:

• This model is suitable for predicting the quality of red wine. For other types of wine, a different model may be needed.
• Results may vary based on the specific dataset and hyperparameter tuning.

🎓 Learning Resources:

• Random Forest Classifier Documentation
• Wine Quality Dataset

🤝 Contributions Welcome:

• Feel free to contribute to this project by submitting pull requests.
• Share your feedback and suggestions to improve the model further.

🍷 Enjoy Predicting Red Wine Quality! 🍷🎉