YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
๐ Book Recommendation System using LightFM
This project builds a hybrid book recommendation system using the LightFM library.
It leverages collaborative and content-based filtering to suggest books to users based on ratings data.
๐ฆ Dataset
- Source: Goodbooks-10K Dataset
- Files used:
books.csv,ratings.csv
๐ง Libraries
pandas,numpy,matplotliblightfm
๐ฎ Recommendation Logic
- Trained a LightFM model using WARP loss function.
- Built a user-item interaction matrix.
- Predicted books that the user hasn't rated yet.
- Displayed top-N recommendations per user.
๐ Visualization
- Bar chart of top 10 most-rated books.
๐ How to Run
pip install -r requirements.txt
jupyter notebook Book_Recommendation_LightFM.ipynb
โ๏ธ Author
Hande รarkcฤฑ
MฤฐT licance
eฤitim amaclฤฑ ve Streamlit uygulamanda bu modeli kullandฤฑm
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐ Ask for provider support