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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.