msjbear / jdata-spark

Related projects: ⓘ

• titicaca / spark-gbtlr
  Hybrid model of Gradient Boosting Trees and Logistic Regression (GBDT+LR) on Spark
  ☆88Updated 5 years ago
• neal668 / GBDT-FM
  An implementation of GBDT+FM
  ☆24Updated 7 years ago
• wangkobe88 / Earth
  ☆27Updated 6 years ago
• lujinhong / ffm
  ☆22Updated this week
• zldeng / XgboostAndLR
  use xgboost and lr model for text classification. xgboost is used to be a feature transform for LR
  ☆44Updated 6 years ago
• wadeallstar / spark
  ☆24Updated 8 years ago
• kunguang / SelectFeature
  主要解决ctr预估工程中的特征选择，特征编号(特征离散),单特征auc和logloss这3个问题.
  ☆20Updated 7 years ago
• hibayesian / spark-fm
  A parallel implementation of factorization machines based on Spark
  ☆73Updated 4 years ago
• sjtuhzc / CTR-estimator
  LR and FM (with sgd or ftrl) model
  ☆25Updated 8 years ago
• weiweijiuzaizhe / ctr_pipeline
  通过对于现有开源分布式机器学习工具的整合(主要是基于参数服务器的logistic regression,xgboost,FFM,FM ),打造一个工业级的,可以线上使用的点击率预估流水线
  ☆26Updated 7 years ago
• jizhihui / fm_python
  implement fm demo with python
  ☆52Updated 5 years ago
• godkillok / tensorflow_template
  ☆14Updated 6 years ago
• QingqingSUN / YoutubeNet
  recommendation system with Youtube Deep Net
  ☆82Updated 6 years ago
• allwefantasy / spark-deep-learning
  Deep Learning Pipelines for Apache Spark
  ☆58Updated 6 years ago
• analysys / 2018_Analysys_2nd_Algorithm_Competition
  2018第二届易观算法大赛
  ☆84Updated 5 years ago
• CastellanZhang / alphaFM_softmax
  Multi-thread implementation of Factorization Machines with FTRL for multi-class classification problem which uses softmax as hypothesis.
  ☆70Updated 3 years ago
• yangxudong / papers
  算法相关的各种论文和slides
  ☆42Updated 5 years ago
• wangruichens / recsys
  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。
  ☆101Updated 4 years ago
• Tristan-Chow / Recommendation-System-based-on-TensorFlow
  Neural candidates generation network based on Youtube reommender paper
  ☆19Updated 5 years ago
• andyxzq / gbdt_lr_in_recsys
  Using gbdt+lr in recommend system and comparing the auc of lr, gbdt, gbdt+lr.
  ☆24Updated 7 years ago
• keyunluo / Tencent2018_Lookalike_Rank10th
  2018年腾讯广告算法大赛Rank10代码：深度部分
  ☆68Updated 6 years ago
• ymkigeg / tensorflow_serving
  show how to use tensorflow estimator train and export model, then serving model and call for prediction
  ☆25Updated last year
• Orisun / ffm
  ☆22Updated 6 years ago
• SongDark / libffm_converter
  ☆18Updated 6 years ago
• andrew-zzz / tree-based-deep-model
  it's the realization of Tree-based Deep Model with tensorflow
  ☆32Updated 4 years ago
• charleshm / deep-ctr
  ☆91Updated 6 years ago
• guojiasheng / gbdt
  gdbt implement by scikit-learn
  ☆25Updated 7 years ago
• zsyandjyhouse / TencentAD_contest
  第一届腾讯社交广告算法大赛
  ☆41Updated 7 years ago
• CastellanZhang / lambdaFM
  Multi-thread implementation of lambdaFM with FTRL for ranking problem. LambdaFM is a learning-to-rank algorithm by combining LambdaRank a…
  ☆111Updated 3 years ago
• HouJP / news-recommendation
  News recommendation system based on spark.
  ☆47Updated 7 years ago