recommand
推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction
🚁🚀基于Flink实现的商品实时推荐系统。flink统计商品热度,放入redis缓存,分析日志信息,将画像标签和实时记录放入Hbase。在用户发起推荐请求后,根据用户画像重排序热度榜,并结合协同过滤和标签两个推荐模块为新生成的榜单的每一个产品添加关联产品,最后返回新的用户列表。
计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估
A unified, comprehensive and efficient recommendation library
Recommendation Algorithm大规模推荐算法库,包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM,DSIN,SIGN,IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESM…
Use Jupyter Notebooks to demonstrate how to build a Recommender with Apache Spark & Elasticsearch
GRU4Rec is the original Theano implementation of the algorithm in "Session-based Recommendations with Recurrent Neural Networks" paper, published at ICLR 2016 and its follow-up "Recurrent Neural Ne…
A TensorFlow recommendation algorithm and framework in Python.
推荐系统入门教程,在线阅读地址:https://datawhalechina.github.io/fun-rec/
rater, recommender systems. 推荐模型,包括:DeepFM,Wide&Deep,DIN,DeepWalk,Node2Vec等模型实现,开箱即用。
Pytorch🍊🍉 is delicious, just eat it! 😋😋