Personalized Recommendation Engine

A hybrid recommendation system combining collaborative and content-based filtering, built with Python, Pandas, Scikit-learn, and Streamlit.

🚀 Features

• Collaborative filtering (user-item interactions)
• Content-based filtering (item categories/metadata)
• Interactive Streamlit dashboard
• Sample dataset included for quick testing

📂 Project Structure

├── app.py                # Streamlit dashboard
├── recommender.py        # Hybrid recommendation system logic
├── data/sample_data.csv  # Example dataset
├── requirements.txt      # Dependencies
└── README.md             # Project documentation

⚡ Usage

1. Clone the repo:

   git clone https://github.com/your-username/Personalized-Recommendation-Engine.git
   cd Personalized-Recommendation-Engine

2. Install dependencies:

   pip install -r requirements.txt

3. Run the app:

   streamlit run app.py

🌐 Live Demo

(Deploy on Streamlit Cloud or Render and paste the link here.)

📸 Screenshots

(Add dashboard screenshots here once you run locally.)