This project implements a hybrid book recommender system using content-based filtering and collaborative filtering, built with Python, scikit-learn, and Streamlit.
- 📖 Content-based recommendation using TF-IDF.
- 👥 Collaborative filtering using K-Nearest Neighbors.
- 🔀 Hybrid approach combining both methods.
- 📊 Interactive Streamlit frontend with book images and genres.
- Python
- Pandas, NumPy
- scikit-learn
- Streamlit
- Pickle
- Dataset: [Kaggle - Best Book Ever 2021] https://www.kaggle.com/datasets/shashwatwork/best-book-ever-data-for-2021
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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 preprocessing and model training:
python Hybrid_Rec_System.ipynb -
Start the Streamlit app:
streamlit run app.py