qian135/ctr_model_zoo

some ctr model, implemented by PyTorch, such as Factorization Machines, Field-aware Factorization Machines, DeepFM, xDeepFM, Deep Interest Network

35
/ 100
Emerging

This project helps online advertisers and marketers predict which ads or products a user is most likely to click on. By taking historical user interaction data and ad features, it outputs predictions that help optimize ad display strategies. Anyone managing digital advertising campaigns or recommendation systems would find this useful.

No commits in the last 6 months.

Use this if you need to improve the relevance and performance of your online advertisements or product recommendations by predicting user click-through rates.

Not ideal if you are looking for models beyond click-through rate prediction, such as conversion forecasting or fraud detection.

online-advertising ad-tech recommendation-systems digital-marketing user-engagement
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 8 / 25
Community 18 / 25

How are scores calculated?

Stars

70

Forks

16

Language

Jupyter Notebook

License

Last pushed

Apr 19, 2019

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/qian135/ctr_model_zoo"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.