52 skills found · Page 1 of 2
PaddlePaddle / PaddleRecRecommendation 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
ZiyaoGeng / RecLearnRecommender Learning with Tensorflow2.x
ycjuan / Kaggle 2014 CriteoNo description available
criteo-research / Reco GymCode for reco-gym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising
chengstone / Kaggle Criteo Ctr Challenge This is a kaggle challenge project called Display Advertising Challenge by CriteoLabs at 2014.这是2014年由CriteoLabs在kaggle上发起的广告点击率预估挑战项目。
rambler-digital-solutions / Criteo 1tb BenchmarkBenchmark of different ML algorithms on Criteo 1TB dataset
songgc / Display Advertising ChallengeCriteo/Kaggle Competition of CTR prediction
MLWave / Kaggle CriteoKaggle Criteo https://www.kaggle.com/c/criteo-display-ad-challenge
Lapis-Hong / Wide ResDNNWide and Deep Learning(Wide&ResDNN) for Kaggle Criteo Dataset in tensorflow
criteo / Consul Templaterbconsul-template-like with erb (ruby) template expressiveness
zgcgreat / Ctr Criteokaggle 2014 criteo ctr竞赛方案整理 https://www.kaggle.com/c/criteo-display-ad-challenge
juliandewit / Kaggle CriteoSoftware for the kaggle criteo challenge
chenhuang-learn / Ffmfield-aware factorization machine implemented by java with an experiment using criteo data set.
chenhuang-learn / Ftrlfollow-the-regularized-leader implemented by java, with an example using criteo dataset.
zxxwin / Tf2 Deepfmtensorflow2.0 实现的 DeepFM，使用 Criteo 子数据集加以实践。
pualien / TrackieA Chrome extension to enhance debugging of some frequently-used tag management platforms (Google Tag Manager, Tealium, Commanders Act, DTM) in combination with some frequently-used tags (Google Analytics, Google Analytics 4, GA Audiences, Ddm, Criteo, Adobe Analytics/Omniture, Floodlight, Comscore, Facebook, Bluekai, Youbora, Kinesis, Webtrekk, Segment)
criteo / CriteoDisplayCTR TFOnSparkNo description available
swapniel99 / CriteoA potential 22nd rank solution to Criteo Labs Display Advertising Challenge on Kaggle
kastnerkyle / Kaggle CriteoCode for Criteo competition http://www.kaggle.com/c/criteo-display-ad-challenge
ivanliu1989 / Predict Click Through Rates On Display AdsDisplay advertising is a billion dollar effort and one of the central uses of machine learning on the Internet. However, its data and methods are usually kept under lock and key. In this research competition, CriteoLabs is sharing a week’s worth of data for you to develop models predicting ad click-through rate (CTR). Given a user and the page he is visiting, what is the probability that he will click on a given ad? The goal of this challenge is to benchmark the most accurate ML algorithms for CTR estimation. All winning models will be released under an open source license. As a participant, you are given a chance to access the traffic logs from Criteo that include various undisclosed features along with the click labels.
