Update README.md

README.md

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+# Hybrid Book Recommender System
+
+This is a **Hybrid Recommendation System** deployed on Hugging Face Spaces using **Gradio**.  
+It combines **Collaborative Filtering (SVD++)** and **Content-Based Filtering** to recommend books to users, even if they are new to the system (cold-start support).  
+
+🔗 **Live Demo**: [Check it out on Hugging Face Spaces](https://huggingface.co/spaces/khalednabawi11/Book-Recommender-System)  
+
+---
+
+## Features
+
+- **Hybrid Model**: Combines collaborative filtering and content-based filtering for more accurate recommendations.  
+- **Cold Start Ready**: Recommends top-rated books to new users with no prior ratings.  
+- **Book Covers**: Shows book covers alongside titles for a more visual experience.  
+- **Gradio**: Backend runs on FastAPI, frontend built with Gradio for an interactive experience.  
+- Model loaded from Kaggle Models using `kagglehub`.  
+
+---
+
+## How It Works
+
+1. **For registered users**:
+   - Predicts ratings for books the user hasn’t rated yet.
+   - Shows the top N books sorted by predicted rating.
+
+2. **For new users**:
+   - Recommends globally top-rated books as a fallback (cold start).  
+
+3. **Visual Output**:
+   - Book title, predicted rating, and cover image in a neat table.
+
+---
+
+## Project Structure
+
+---
+├── app.py # Main Gradio app
+├── requirements.txt # Dependencies
+├── README.md
+├── books-recomendation-system-0.ipynb => Model Development Notebook
+---
+
+
+
+
+## Setup Locally
+
+Clone the repo and run:  
+
+```bash
+pip install -r requirements.txt
+python app.py
+```
+
+##  Dependencies
+
+```
+- gradio
+- pandas
+- numpy
+- scikit-learn
+- kagglehub
+- surprise (for SVD++ model)
+- fastapi
+- uvicorn
+```
+
+## Model Details
+
+- Collaborative Filtering: SVD++ trained on user-item ratings.
+- Content-Based Filtering: Uses book metadata (title, genres, etc.).
+- Hybrid approach balances both for better personalization.
+
+
+## Deployment
+```
+This app is deployed on Hugging Face Spaces using Gradio UI and loads the model directly from Kaggle Models via kagglehub.
+```
+
+
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference