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🌸 About the Project Iris Flower Prediction ML App is a web-based machine learning application built using Django and scikit-learn. It predicts the species of an Iris flower β€” Setosa, Versicolor, or Virginica β€” based on the input of four numeric features: sepal length, sepal width, petal length, and petal width.

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ShrishMaruge/iris-prediction-ml-django

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🌸 Iris Flower Prediction - ML Web App (Django)

License Python Framework ML Deploy

A modern, user-friendly web application built using Django and scikit-learn to predict the species of Iris flowers (Setosa, Versicolor, Virginica) based on input parameters: sepal length, sepal width, petal length, and petal width.


πŸ”— Live Demo

Deploy to Render

🌐 View the Project Live


πŸš€ Features

  • 🌼 Predicts Iris species in real-time from four input features.
  • πŸ”¬ Integrated ML model trained on Iris Dataset (UCI Repository).
  • πŸ“ˆ Highly accurate predictions using Random Forest or Logistic Regression.
  • πŸ–₯️ Intuitive and clean Bootstrap-powered web interface.
  • πŸ“‚ Optional CSV input extension ready for batch prediction.
  • πŸ›  Easily extendable for more features or UI enhancements.
  • πŸ”’ Secure input handling and form validation.
  • πŸ“Š Optionally add visual graphs for feature importance/predictions.

πŸ“Έ Screenshots

Prediction Form

Prediction Result


🧠 Tech Stack

Technology Purpose
Python Core language
Django Web framework (MVC)
scikit-learn Machine Learning model training
joblib Model serialization
HTML/CSS Web UI
Bootstrap Responsive styling

πŸ“„ License

This project is licensed under the Apache License 2.0 Β© 2025 Shrish Maruge.
Feel free to use, modify, and distribute β€” with proper attribution.


βš™οΈ Setup Instructions

πŸ”§ Prerequisites

  • Python 3.7–3.11 installed
  • git installed
  • Internet connection for package install

πŸ› οΈ Installation Steps

# Clone the repo
git clone https://github.com/your-username/iris-prediction-ml-django.git
cd iris-prediction-ml-django

# Create and activate a virtual environment
python -m venv venv
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

# Install required packages
pip install -r requirements.txt

# Start the development server
python manage.py runserver

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About

🌸 About the Project Iris Flower Prediction ML App is a web-based machine learning application built using Django and scikit-learn. It predicts the species of an Iris flower β€” Setosa, Versicolor, or Virginica β€” based on the input of four numeric features: sepal length, sepal width, petal length, and petal width.

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