https://github.com/kunalpisolkar24/winequalityprediction
Predicting wine quality using machine learning with matplotlib, numpy, pandas, and seaborn for insightful data analysis. 🍇🤖📊
https://github.com/kunalpisolkar24/winequalityprediction
data-analysis data-science data-visualization machine-learning prediction-model
Last synced: about 1 month ago
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Predicting wine quality using machine learning with matplotlib, numpy, pandas, and seaborn for insightful data analysis. 🍇🤖📊
- Host: GitHub
- URL: https://github.com/kunalpisolkar24/winequalityprediction
- Owner: kunalPisolkar24
- License: mit
- Created: 2024-01-08T17:14:42.000Z (almost 2 years ago)
- Default Branch: master
- Last Pushed: 2024-01-10T13:49:31.000Z (almost 2 years ago)
- Last Synced: 2025-03-05T17:39:59.435Z (9 months ago)
- Topics: data-analysis, data-science, data-visualization, machine-learning, prediction-model
- Language: Jupyter Notebook
- Homepage:
- Size: 3.01 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# Wine Quality Prediction Project
## Table of Contents
- Introduction
- Installation
- Usage
- Contributions
- License
## Introduction
This project aims to predict the quality of wine based on various physicochemical properties. The dataset used in this project contains 1599 entries and 13 columns, each representing a different property of the wine.
## Installation
The project requires the following Python libraries: numpy, matplotlib, pandas, seaborn, and warnings. You can install these using pip:
```bash
pip install numpy matplotlib pandas seaborn jupyter
```
# Usage
After installing the necessary libraries, you can clone this repository and run the main script:
```bash
https://github.com/kunalPisolkar24/wineQualityPrediction.git
cd wineQualityPrediction
jupyter Wine_Quality.ipynb
```
🤝 **Contributions:**
Contributions from students, educators, and enthusiasts are highly encouraged. If you have additional practicals, improvements, or fixes to share, feel free to open a pull request. Please adhere to the contribution guidelines in [CONTRIBUTING.md](./CONTRIBUTING.md).
📄 **License:**
This repository is licensed under the [MIT License](./LICENSE). You are free to use, modify, and distribute the code for academic and personal purposes.