Book Recommender System using Collaborative Filtering

This repository contains a collaborative filtering-based book recommender system built with Python Flask. The recommender system utilizes cosine similarity to suggest books based on user preferences and historical data.

Features

• Collaborative filtering algorithm for personalized recommendations.
• Utilizes cosine similarity for efficient book similarity calculations.
• User-friendly interface built with Flask for easy interaction.

Requirements

• Python 3.x
• Flask
• Pandas
• NumPy
• scikit-learn

Installation

1. Clone the repository: git clone https://github.com/your_username/book-recommender.git
2. Navigate to the project directory: cd book-recommender
3. Install dependencies: pip install -r requirements.txt

Usage

1. Run the Flask app: python app.py
2. Access the book recommender system in your web browser at http://localhost:5000

How it Works

The recommender system analyzes user book ratings and similarities between books using cosine similarity. Based on this analysis, it generates personalized recommendations for users.

Future Improvements

• Integration with additional data sources for broader book recommendations.
• Enhanced user interface with improved design and usability.
• Implementation of more advanced recommendation algorithms.

Contributions

Contributions are welcome! Feel free to submit issues, feature requests, or pull requests to help improve the project.