A framework for large scale recommendation algorithms.
APACHE-2.0 License
EasyRec implements state of the art deep learning models used in common recommendation tasks: candidate generation(matching), scoring(ranking), and multi-task learning. It improves the efficiency of generating high performance models by simple configuration and hyper parameter tuning(HPO).
Running Platform:
Any contributions you make are greatly appreciated!
If EasyRec is useful for your research, please cite:
@article{Cheng2022EasyRecAE,
title={EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems},
author={Mengli Cheng and Yue Gao and Guoqiang Liu and Hongsheng Jin and Xiaowen Zhang},
journal={ArXiv},
year={2022},
volume={abs/2209.12766}
}
EasyRec is released under Apache License 2.0. Please note that third-party libraries may not have the same license as EasyRec.