Books-Recommendation-System.

A collaborative filtering-based recommendation system that suggests 4-5 similar books to the user based on their selection. The web app is built with Flask and uses cosine similarity on preprocessed book data to recommend titles.

How it works:

-Dataset is preprocessed (removing duplicates, cleaning, and structuring).

-A cosine similarity matrix is created based on user-book interactions.

-When a user selects a book, the system finds the most similar books using collaborative filtering.

-Flask serves the recommendations on a user-friendly web page.

Demo:

Demo is in the folder named 'demo images' in this repo.

Installation:

# Clone the repository git clone https://github.com/YourUsername/Books-Recommendation-System.git

Navigate to the project directory -cd Books-Recommendation-System

Install dependencies -pip install -r requirements.txt

Run the Flask app -python app.py

Future Improvements

-Use content-based filtering (book genres, authors, keywords)

• Hybrid model (collaborative + content-based)

• Improve UI/UX with better frontend design

• Deploy on Heroku/Render/Streamlit Cloud

🤝 Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you’d like to change.