Topic: gru4rec Goto Github
Some thing interesting about gru4rec
Some thing interesting about gru4rec
gru4rec,Keras implementation of the GRU4Rec recommendation algorithm.
User: flowel1
gru4rec,Jupyter тетрадка с решением Kaggle соревнования Alfa Campus
User: mark-narusov
Home Page: https://www.kaggle.com/competitions/alfabank-campus/overview
gru4rec,⚡️ Implementation of TRON: Transformer Recommender using Optimized Negative-sampling, accepted at ACM RecSys 2023.
Organization: otto-de
Home Page: https://arxiv.org/abs/2307.14906
gru4rec,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、ESMM、ESCMM, MAML、xDeepFM、DeepFEFM、NFM、AFM、RALM、DMR、GateNet、NAML、DIFM、Deep Crossing、PNN、BST、AutoInt、FGCNN、FLEN、Fibinet、ListWise、DeepRec、ENSFM,TiSAS,AutoFIS等,包含经典推荐系统数据集criteo 、movielens等
Organization: paddlepaddle
Home Page: https://paddlerec.readthedocs.io/
gru4rec,PyTorch implementation of GRU4Rec, SQN and SMORL with evaluation framework covering Hit-Ratio, NDCG, Novelty, Diversity and Repetitiveness metrics for top-k recommendations.
User: patricksvm
gru4rec,Several sequential recommended models implemented by tenosrflow1.x
User: slientge
gru4rec,用pytorch 方法复现了二十多个经典的推荐算法论文,其中包含排序论文和推荐召回论文,并在demo里面选了一个召回模型和排序模型的运行示例。
User: yinzhenwan
Home Page: https://github.com/YinzhenWan/recome_wan
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