nbsps / SilvensnRecSys
Primary Recommender System: online[matching|ranking...](Flask|Vue) - nearline[model serving|real-time service](Flink|tensorflow serving|redis) - offline[feature engine|model training](Spark|Hdfs(Hbase)|tf)
☆12Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for SilvensnRecSys
- 一个基于 fasttext + faiss 的商品内容相关推荐实现,nginx+uwsgi+flask / gunicorn+uvicorn+fastapi 提供api查询接口,增加Spark实现 Ansj+Word2vec+LSH+Phoenix☆48Updated last year
- 基于wide deep模型的CTR预估,从训练到部署☆15Updated 5 years ago
- rater, recommender systems. 推荐模型,包括:DeepFM,Wide&Deep,DIN,DeepWalk,Node2Vec等模型实现,开箱即用。☆41Updated 4 years ago
- tensorflow2.0 实现的 DeepFM,使用 Criteo 子数据集加以实践。☆29Updated 4 years ago
- 用PaddlePaddle实现的真实案例和有趣应用☆23Updated 5 years ago
- 推荐算法学习☆38Updated last year
- Recommender system based on Flink and Reinforcement Learning☆99Updated 4 years ago
- 基于TensorFlow实现推荐系统的model☆12Updated 9 months ago
- 短视频内容理解与推荐竞赛☆82Updated 4 years ago
- Impementation paper "Deep Neural Networks for YouTube Recommendations"☆74Updated 4 years ago
- 简单的实现推荐系统的召回模型和排序模型,其中召回模型使用协同过滤算法,排序模型使用gbdt+lr算法☆58Updated 5 years ago
- This repository provides a comprehensive implementation of a deep neural network-based recommendation system similar to YouTube's. The re…☆52Updated last month
- YouTube推荐算法☆105Updated 2 years ago
- 阿里巴巴ESMM模型解读☆35Updated 4 years ago
- ☆57Updated last year
- 阿里DIEN与DIN Tensorflow2.0 复现☆52Updated 4 years ago
- 推荐系统相关模型 包括召回和排序☆30Updated 4 years ago
- 基于ESMM、MMoE和deepFM的多目标模型☆23Updated 2 years ago
- 2017“达观杯”个性化 推荐算法挑战赛-rank6☆43Updated 5 years ago
- 零售电商客户流失模型,基于tensorflow,xgboost4j-spark,spark-ml实现LR,FM,GBDT,RF,进行模型效果对比,离线/在线部署方式总结☆66Updated last year
- esmm model by tensorflow keras☆64Updated 3 years ago
- 讯飞移动广告反欺诈算法竞赛☆31Updated 5 years ago
- 第三届 Apache Flink 极客挑战赛暨AAIG CUP——电商推荐“抱大腿”攻击识别亚军代码方案☆28Updated 2 years ago
- show how to use tensorflow estimator train and export model, then serving model and call for prediction☆25Updated last year
- LR, FM, DeepFM, xDeepFM, DIN, CF等推荐算法代码demo。采用TFRecords作为输入,方便实际场景应用。☆102Updated 4 years ago
- ☆13Updated 3 years ago
- 短视频 youtube召回模型推荐,特征包括标题 tags id,tfserving docker部署☆23Updated 3 years ago
- 一些CTR模型和常见特征工程的方法☆25Updated 3 years ago