A comprehensive full-stack web application featuring multiple AI/ML models for predictions, classifications, and intelligent analysis.
Features • Models • Installation • Tech Stack• Tech Stack • Contact
| Model | Type | Task | Technology | Status |
|---|---|---|---|---|
| 🩺 Cancer Prediction | Classification | Medical diagnosis prediction | RandomForest / XGBoost | ✅ Active |
| 🚗 Car Price Prediction | Regression | Vehicle valuation | RandomForest / XGBoost | ✅ Active |
| 🏠 House Price Prediction | Regression | Real estate valuation | RandomForest / XGBoost | ✅ Active |
| 🎓 Student Performance | Regression | Academic outcome prediction | RandomForest / XGBoost | ✅ Active |
| 🍷 Wine Quality Assessment | Classification | Wine quality grading | RandomForest / XGBoost | ✅ Active |
| 📧 Email Classification | NLP Classification | Spam/category detection | TensorFlow Transformers | ✅ Active |
| 📄 PDF Summarization | NLP Summarization | Document summarization | BART (facebook/bart-large-cnn) | ✅ Pre-trained |
- Python 3.9.13
- pip package manager
- Virtual environment (recommended)
1️⃣ Clone the Repository
git clone https://github.com/yourusername/ai-model-hub.git
cd ai-model-hub2️⃣ Create Virtual Environment
python -m venv venv3️⃣ Activate Virtual Environment
# Windows
venv\Scripts\activate
# macOS/Linux
source venv/bin/activate4️⃣ Install Dependencies
pip install -r requirements.txt
⚠️ Important: Strictly follow the dependency versions specified inrequirements.txtto ensure compatibility.
5️⃣ Run the Application
python app.py6️⃣ Access the Application
Open your browser and navigate to: http://localhost:5000 <=== in here, actually, any available port that your local has.
Python==3.9.13
Flask==3.1.2
tensorflow==2.10.1
scikit-learn==1.6.1
pandas==2.3.3
numpy==1.26.4
matplotlib==3.9.4
seaborn==0.13.2
h5py==3.14.0
joblib==1.5.3
transformers==latest💡 Note: These exact versions are required for optimal performance and compatibility.
AI_Model_Hub/
├── app.py # Flask application with route handlers
├── templates/ # HTML templates
│ ├── index.html # Main landing page
│ ├── cancer.html # Cancer prediction interface
│ ├── car.html # Car price prediction
│ ├── house.html # House price prediction
│ ├── student.html # Student performance
│ ├── wine.html # Wine quality assessment
│ ├── email.html # Email classification
│ └── upload_pdf.html # PDF summarization
├── static/
│ └── images/ # UI screenshots
├── deeplearning_models/ # Trained model files (.pkl, .h5)
├── supervised_models/ # Trained model files (.joblib)
├── requirements.txt # Python dependencies
└── README.md # Project documentation
This project is licensed under the MIT License - see the LICENSE file for details.
MIT License
Copyright (c) 2024 Thonedra
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files...
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