https://github.com/shamikaredkar/redwinequality-mlproject

The project applied machine learning to predict red wine quality using the UCI dataset. Key steps included data exploration, model selection (with a focus on a stacking classifier), and evaluation using metrics like F1 Score. Feature importance was also analyzed for insights.
https://github.com/shamikaredkar/redwinequality-mlproject

data-science jupyter-notebook machine-learning machine-learning-algorithms python red-wine-quality-dataset

Last synced: 3 months ago
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The project applied machine learning to predict red wine quality using the UCI dataset. Key steps included data exploration, model selection (with a focus on a stacking classifier), and evaluation using metrics like F1 Score. Feature importance was also analyzed for insights.

• Host: GitHub
• URL: https://github.com/shamikaredkar/redwinequality-mlproject
• Owner: shamikaredkar
• License: mit
• Created: 2023-12-04T17:15:16.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-01-17T22:39:32.000Z (over 2 years ago)
• Last Synced: 2025-12-29T23:04:01.999Z (7 months ago)
• Topics: data-science, jupyter-notebook, machine-learning, machine-learning-algorithms, python, red-wine-quality-dataset
• Language: Jupyter Notebook
• Homepage:
• Size: 2.47 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
[](https://rishavchanda.io)



    
Red Wine Quality Predictor

    
This project utilizes machine learning techniques to predict the quality of red wine based on various physicochemical properties. It aims to provide valuable insights for wine enthusiasts and producers, and demonstrate the potential of data science in the field of oenology.





    
Usage Instructions

    
Run the Jupyter Notebook to start the analysis. The notebook is structured to guide you through the data preprocessing, model training, and evaluation stages.





    
Results and Interpretation

    
The notebook provides visualizations and statistical outputs to interpret the quality of red wine. Make sure to read the descriptions and interpretations provided to understand the results fully.





    
License Information

    
This project is licensed under the MIT License. See the LICENSE file in the repository for full license text.