Book Recommendation System

This Book Recommendation System suggests books based on a selected title, displaying recommended titles along with their cover images.

Project Structure

• app.py: The main Streamlit application file.
• artifacts/: Directory containing pre-trained models and data files.
  • modal.pkl: Pre-trained model for book recommendations.
  • books_name.pkl: List of book names for the recommendation selection.
  • final_rating.pkl: Dataframe with book ratings and image URLs.
  • book_pivot.pkl: Book-pivot table for recommendation calculations.

Setup and Installation

Prerequisites

• Python 3.8+
• Streamlit

Installation Steps

1. Clone the repository:

   git clone https://github.com/your-username/Book-Recommendation-System.git
   cd Book-Recommendation-System

2. Install dependencies: Ensure that requirements.txt is in the project directory, then run:

   pip install -r requirements.txt

3. Ensure all required data files are in place: Place the following files in an artifacts folder:

   • modal.pkl
   • books_name.pkl
   • final_rating.pkl
   • book_pivot.pkl

4. Run the Streamlit app: Start the app by running:

   streamlit run app.py

5. Using the Application:

   • Open the provided local URL in your browser.
   • Select a book from the dropdown menu and click Recommend to see book suggestions with their cover images.

Troubleshooting

• If you encounter a FileNotFoundError for any .pkl files, ensure they are in the correct path (artifacts folder).
• If dependencies fail to install, confirm that requirements.txt is correctly configured and contains all necessary packages.

Requirements

List of primary dependencies (included in requirements.txt):

• streamlit
• numpy
• pickle (built-in to Python)
• Other dependencies required for model loading and data handling

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Dataset and resources for the recommendation system.
• Streamlit documentation and community for guidance.