This project is a book recommender system designed to help users find books they might enjoy based on their preferences. It uses machine learning algorithms to analyze user input and suggest similar books. The project is implemented using Python, Flask for backend logic, and Bootstrap for frontend styling.
- Top 50 Highest-Rated Books: Display the top 50 highest-rated books.
- Personalized Recommendations: Provide personalized book recommendations based on user input.
- Responsive Interface: Designed with Bootstrap for an intuitive and responsive user experience.
This system recommends books based on their popularity, considering the following conditions:
- Books must have at least 250 ratings.
- Books are selected based on the highest average rating.
- The system displays the top 50 books that meet these criteria.
This system provides personalized recommendations based on collaborative filtering, with the following conditions:
- Only users who have rated more than 150 books are considered.
- Only books that have been rated by more than 25 people are included.
- Collaborative filtering algorithms are used to generate recommendations.
Contributions are welcome! If you have suggestions or improvements, please open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for details.
Made with ❤️ by Purval Bhude. For more about me and my work, visit my Portfolio or LinkedIn.