Federated-Recommendation-Neural-Collaborative-Filtering
TIMDB
Our great sponsors
Federated-Recommendation-Neural-Collaborative-Filtering | TIMDB | |
---|---|---|
2 | 1 | |
25 | 35 | |
- | - | |
3.9 | 0.0 | |
about 1 year ago | 11 months ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Federated-Recommendation-Neural-Collaborative-Filtering
-
Federated-Recommendation-Neural-Collaborative-Filtering
AmanPriyanshu/Federated-Recommendation-Neural-Collaborative-Filtering (github.com)
- Made a Federated Learning (Distributed) Setting for Recommendation Systems
TIMDB
-
Are there any downloadable datasets of all tv show/movie metadata including per episode synopsis?
As an example, here is some relevant code I wrote for IMDB. Note that the code is a bit rough as it was written some time ago.
What are some alternatives?
torchrec - Pytorch domain library for recommendation systems
next-movie - Pick your next movie using Next.js 13
LT-OCF - LT-OCF: Learnable-Time ODE-based Collaborative Filtering, CIKM'21
cinemagoer - Cinemagoer is a Python package useful to retrieve and manage the data of the IMDb (to which we are not affiliated in any way) movie database about movies, people, characters and companies
federeco - implementation of federated neural collaborative filtering algorithm
MovieRecommender - 🎥 Movie Recommender AI System
disco - Recommendations for Ruby and Rails using collaborative filtering
PopCritic - Movies Reviewed by people, for people
recommenders - Best Practices on Recommendation Systems
perplex - A Movie Renamer for Plex Metadata
LargeBatchCTR - Large batch training of CTR models based on DeepCTR with CowClip.
watch3r - Movie watchlist and journal app built with Vue 3 and Fauna DB. All future development of this project has moved to Codeberg.