{"id":50885984,"url":"https://github.com/mayank4543/collegeperformance","last_synced_at":"2026-06-15T17:01:58.749Z","repository":{"id":271907418,"uuid":"914181513","full_name":"Mayank4543/CollegePerformance","owner":"Mayank4543","description":"The College Performance and Ranking Application is designed to help students compare colleges based on key parameters such as placement, faculty experience, fees, and average package. 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It also includes a **College Recommendation System** that suggests suitable colleges based on user preferences and **Machine Learning predictions** for ranking analysis.\n\n## 🚀 Features\n\n- 📊 **College Comparison** – Compare colleges side by side with detailed insights.\n- 🤖 **Machine Learning Predictions** – Provides ranking based on past trends and analytics.\n- 🎯 **College Recommendation System** – Suggests colleges based on filters like stream, ratings, placement, and fees.\n- 📈 **Performance Analytics** – Visualizes trends using **Plotly**.\n- 🌐 **User-Friendly UI** – Built with **Flask, HTML, CSS (Tailwind/Sass), and JavaScript**.\n\n## 🏗️ Tech Stack\n\n- **Frontend:** HTML, CSS (Sass), Tailwind CSS, JavaScript\n- **Backend:** Python (Flask)\n- **Database:** CSV Dataset (Can be extended to SQL/NoSQL)\n- **Machine Learning:** KNN, Decision Tree for Recommendation System\n- **Visualization:** Plotly, Matplotlib\n\n## 📂 Project Structure\n\n```\n📦 College-Performance-Ranking\n├── 📁 static              # CSS, JS, Images\n├── 📁 templates           # HTML templates\n├── 📁 models              # ML models for ranking \u0026 prediction\n├── 📄 app.py              # Flask backend\n├── 📄 dataset.csv         # College data\n├── 📄 README.md           # Project documentation\n├── 📄 requirements.txt    # Dependencies\n└── 📄 config.py           # Configurations\n```\n\n## 🛠️ Installation \u0026 Setup\n\n### 1️⃣ Clone the Repository\n\n```bash\ngit clone https://github.com/yourusername/college-ranking-app.git\ncd college-ranking-app\n```\n\n### 2️⃣ Install Dependencies\n\n```bash\npip install -r requirements.txt\n```\n\n### 3️⃣ Run the Application\n\n```bash\npython app.py\n```\n\n### 4️⃣ Open in Browser\n\n```\nhttp://127.0.0.1:5000/\n```\n\n## 📌 How It Works\n\n1. **Select Colleges** – Choose colleges to compare.\n2. **View Insights** – Get details like placement, faculty experience, and fees.\n3. **ML-Based Predictions** – See future performance trends.\n4. **College Recommendation** – Get the best college suggestions.\n\n## 🔮 Future Enhancements\n\n- ✅ **Integrate SQL Database** for efficient data management.\n- ✅ **More ML Algorithms** for better ranking and prediction.\n- ✅ **User Authentication** for personalized college recommendations.\n\n## 💡 Contributing\n\nContributions are welcome! Feel free to fork the repository and create pull requests.\n\n## 📜 License\n\nThis project is licensed under the **MIT License**.\n\n## ✨ Authors\n\n- **Mayank** – [GitHub](https://github.com/yourusername)\n\n---\n\n💡 *For any queries, feel free to reach out!* 🚀\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmayank4543%2Fcollegeperformance","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmayank4543%2Fcollegeperformance","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmayank4543%2Fcollegeperformance/lists"}