This project implements a Book Recommender System using Streamlit, where users can explore popular books, get recommendations based on book similarity scores using collaborative filtering, and manage their "To Read" list.
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Home Page:
- Displays popular books based on average ratings from users who rated more than 250 books.
- Allows users to add books to their "To Read" list.
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Recommendation Page:
- Users can select a book and get recommendations based on similarity scores with other books in the dataset using collaborative filtering.
- Top 4 most similar books are recommended.
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To Read List:
- Displays the list of books added by the user to read.
- Allows users to mark books as read/unread.
- The Home Page showcases popular books based on average ratings from users who have rated more than 250 books. The top 100 most popular books are displayed.
- The Recommendation Page utilizes collaborative filtering to recommend books based on similarity scores between books. It calculates the similarity between selected books and suggests the top 4 most similar books.
- Clone the Repository:
git clone https://github.com/your_username/book-recommender-system.git cd book-recommender-system - Install Dependencies:
pip install -r requirements.txt
- Run the Application:
streamlit run app.py
