🍄 Mushroom Classification & Analysis Web App

Overview

• Interactive web application for mushroom dataset analysis
• Uses machine learning for classification and regression
• Allows users to upload their own data (CSV format)
• Visualizes key features and data distributions
• Helps identify important features for mushroom identification and safety
• Designed for both educational and practical data science use

Key Features

• Upload and analyze mushroom datasets (CSV format)
• Classification (Logistic Regression) and regression (Linear Regression) support
• Visualizations: histograms, KDE plots, pie charts, scatter plots, bar charts, and box plots
• Feature importance and model performance metrics
• Responsive, user-friendly interface with dark mode
• Robust error handling and clear feedback

Technology Stack

• Frontend: HTML5, CSS3, Django Templates
• Backend: Python, Django
• ML & Data Analysis: Pandas, NumPy, scikit-learn, Matplotlib, Seaborn

How to Run

1. Clone the repository and navigate to the project directory.
2. Install dependencies:

   pip install -r requirements.txt

3. Run database migrations:

   python manage.py migrate

4. Start the development server:

   python manage.py runserver

5. Open your browser and go to http://127.0.0.1:8000/

Data Description

The dataset should include features such as cap shape, color, gill characteristics, stalk features, and a target column (e.g., class for classification or a numeric column for regression).

Error Handling

• Validates file type and data integrity
• Handles missing or invalid data gracefully
• Displays user-friendly error messages in the interface

License

This project is for educational and research purposes.