| recommenders-team/recommenders |
17,440 |
|
0 |
2 |
about 2 years ago |
11 |
April 01, 2022 |
169 |
mit |
Python |
| Best Practices on Recommendation Systems |
| cheungdaven/DeepRec |
1,068 |
|
0 |
0 |
almost 4 years ago |
0 |
|
8 |
gpl-3.0 |
Python |
| An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow. |
| caserec/Datasets-for-Recommender-Systems |
821 |
|
0 |
0 |
over 2 years ago |
0 |
|
1 |
|
Jupyter Notebook |
| This is a repository of a topic-centric public data sources in high quality for Recommender Systems (RS) |
| guymorita/recommendationRaccoon |
690 |
|
26 |
4 |
over 6 years ago |
19 |
March 06, 2017 |
19 |
mit |
JavaScript |
| A collaborative filtering based recommendation engine and NPM module built on top of Node.js and Redis. The engine uses the Jaccard coefficient to determine the similarity between users and k-nearest-neighbors to create recommendations. This module is useful for anyone with a database of users, a database of products/movies/items and the desire to give their users the ability to like/dislike and receive recommendations. |
| zygmuntz/goodbooks-10k |
576 |
|
0 |
0 |
over 7 years ago |
0 |
|
1 |
other |
Jupyter Notebook |
| Ten thousand books, six million ratings |
| shenweichen/DSIN |
405 |
|
0 |
0 |
almost 3 years ago |
0 |
|
5 |
apache-2.0 |
Python |
| Code for the IJCAI'19 paper "Deep Session Interest Network for Click-Through Rate Prediction" |
| caserec/CaseRecommender |
367 |
|
0 |
0 |
over 4 years ago |
42 |
November 25, 2021 |
4 |
mit |
Python |
| Case Recommender: A Flexible and Extensible Python Framework for Recommender Systems |
| hwwang55/RippleNet |
347 |
|
0 |
0 |
over 6 years ago |
0 |
|
9 |
mit |
Python |
| A tensorflow implementation of RippleNet |
| DataSystemsLab/recdb-postgresql |
262 |
|
0 |
0 |
almost 6 years ago |
0 |
|
10 |
|
C |
| RecDB is a recommendation engine built entirely inside PostgreSQL |
| GHamrouni/Recommender |
249 |
|
0 |
0 |
over 3 years ago |
0 |
|
1 |
bsd-2-clause |
C |
| A C library for product recommendations/suggestions using collaborative filtering (CF) |
