Welcome to the "Book Recommender System" project! This collaborative recommender system uses the K-Nearest Neighbors (KNN) algorithm to recommend books based on user preferences. Explore new books you'll love!
Recommender systems are a type of software application that provide personalized recommendations to users. These recommendations are based on user behavior and preferences. The "Book Recommender System" is a collaborative recommender system, which means it provides recommendations by finding users who are similar to you and suggesting books that they have liked.
The "Book Recommender System" uses a powerful algorithm called K-Nearest Neighbors (KNN). This algorithm finds books similar to the ones you've liked by analyzing the preferences of other users. It takes into account the ratings and reviews you've provided and finds books with similar ratings from other users. The more you rate and review books, the more accurate the recommendations become.
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Personalized Recommendations: Get book recommendations tailored to your reading habits and interests.
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User Ratings: Rate and review books to enhance the system's recommendation accuracy.
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Collaborative Filtering: Utilizes collaborative filtering with KNN to recommend books similar to your favorites.
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Interactive Interface: The web-based interface provides a seamless user experience.
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Deployment: Hosted on Streamlit for easy accessibility.
This project leverages the following technologies:
To run this project locally, follow these steps:
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Clone the repository to your local machine using this command:
git clone https://github.com/rajatrawal/book-recommender-system-1.git
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Navigate to the project directory:
cd book-recommender-system-1 -
Install the required Python libraries:
pip install -r requirements.txt
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Run the Streamlit app locally:
streamlit run app.py
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Open the provided local URL in your web browser to access the Book Recommender System.
Explore the "Book Recommender System" and discover new books that match your interests. Dive into the world of literature with personalized book recommendations. Visit the Live Demo and embark on a reading adventure.
If you'd like to contribute to this project or have suggestions for improvement, please feel free to submit issues or pull requests on GitHub.
Thank you for exploring the "Book Recommender System"! We hope this system enriches your reading experience. 📚🌟