This repository contains a Python-based book recommendation system that utilizes machine learning techniques to provide personalized book suggestions. The project employs a popularity-based recommendation approach, collaborative filtering, and a hybrid model to deliver tailored recommendations.
- Popularity-Based Recommendations: Suggests books based on the average rating and number of reviews, prioritizing books with at least 250 ratings.
- Collaborative Filtering: Recommends books based on user similarity, accounting for ratings given by similar users.
- Hybrid Recommendations: Combines popularity and collaborative filtering for more robust suggestions.
- Web Interface: Uses Flask to provide a simple interface for interacting with the recommendation system.
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Clone the repository:
git clone https://github.com/Aarush-Parashar/book-recommender.git
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Navigate to the project directory:
cd book-recommender -
Install dependencies:
pip install -r requirements.txt
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Run the application:
python app.py
- Start the server using the command above.
- Interact with the recommendation system by entering user preferences or viewing popular books.
- app.py: Main file for running the Flask web server.
- models/: Contains data processing and recommendation models.
- templates/: HTML templates for the web interface.
- static/: Static files, including CSS for the web app.
Contributions are welcome! Please feel free to submit a pull request or open an issue to discuss improvements, new features, or bug fixes.