🌸 Iris Visual AI

Real-time Iris flower species classifier with interactive 3D visualization
Built by Yathik · RyStudios

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🚀 Live Demo

Layer	URL
🌐 Frontend	https://iris-visual-ai-frontend.vercel.app
⚙️ Backend API	https://iris-visual-ai-api.onrender.com

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✨ Features

• 🤖 ML model trained on the classic Iris dataset
• 📊 Interactive 3D Plotly scatter plots
• ⚡ Real-time species prediction with probability scores
• 🎯 Highlights your input point live in the 3D chart
• 🌙 Sleek dark UI with smooth animations

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🛠️ Tech Stack

Layer	Tech
Frontend	HTML, CSS, Vanilla JS, Plotly.js
Backend	Python, FastAPI, Uvicorn
ML Model	Scikit-learn, Joblib
Deploy Frontend	Vercel (Free)
Deploy Backend	Render (Free)

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📁 Project Structure

IRIS_JS_APP_FAST_API/
├── backend/
│   ├── api.py
│   ├── iris_model.joblib
│   ├── iris_scaler.joblib
│   ├── iris_label_encoder.joblib
│   └── requirements.txt
├── frontend/
│   ├── index.html
│   ├── main.js
│   └── style.css
├── render.yaml
├── vercel.json
└── README.md

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⚙️ Run Locally

Backend

cd backend
pip install -r requirements.txt
uvicorn api:app --reload --port 8001

Frontend

# Just open frontend/index.html in browser
# Or use Live Server in VS Code

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🎬 Part of RyStudios App Suite

This is App #1 of many ML projects under the RyStudios portfolio.

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© 2025 Yathik · RyStudios. All rights reserved.