ctr-prediction
There are 112 repositories under ctr-prediction topic.
wzhe06/Ad-papers
Papers on Computational Advertising
RUCAIBox/RecBole
A unified, comprehensive and efficient recommendation library
ChenglongChen/tensorflow-DeepFM
Tensorflow implementation of DeepFM for CTR prediction.
mJackie/RecSys
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
ZiyaoGeng/RecLearn
Recommender Learning with Tensorflow2.x
alibaba/EasyRec
A framework for large scale recommendation algorithms.
rixwew/pytorch-fm
Factorization Machine models in PyTorch
reczoo/FuxiCTR
A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io
qiaoguan/deep-ctr-prediction
CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)
wzhe06/SparkCTR
CTR prediction model based on spark(LR, GBDT, DNN)
lambdaji/tf_repos
TensorFlow Script
DataCanvasIO/DeepTables
DeepTables: Deep-learning Toolkit for Tabular data
UlionTse/mlgb
MLGB is a library that includes many models of CTR Prediction & Recommender System by TensorFlow & PyTorch. MLGB是一个包含50+点击率预估和推荐系统深度模型的、通过TensorFlow和PyTorch撰写的库。
mengfeizhang820/Paperlist-for-Recommender-Systems
Recommender Systems Paperlist that I am interested in
datawhalechina/torch-rechub
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
DSXiangLi/CTR
CTR模型代码和学习笔记总结
Atomu2014/product-nets
Tensorflow implementation of Product-based Neural Networks. An extended version is at https://github.com/Atomu2014/product-nets-distributed.
chenxijun1029/DeepFM_with_PyTorch
A PyTorch implementation of DeepFM for CTR prediction problem.
reczoo/BARS
BARS: Towards Open Benchmarking for Recommender Systems https://openbenchmark.github.io/BARS
archersama/awesome-recommend-system-pretraining-papers
Paper List for Recommend-system PreTrained Models
huangsg1/uncertainty-calibration
A collection of research and application papers of (uncertainty) calibration techniques.
easezyc/Multitask-Recommendation-Library
MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets.
Lapis-Hong/wide_deep
Wide and Deep Learning for CTR Prediction in tensorflow
ChenglongChen/tensorflow-XNN
4th Place Solution for Mercari Price Suggestion Competition on Kaggle using DeepFM variant.
GitHub-HongweiZhang/prediction-flow
Deep-Learning based CTR models implemented by PyTorch
ustcml/RecStudio
A highly-modularized and recommendation-efficient recommendation library based on PyTorch.
HaSai666/rec_pangu
rec_pangu is a flexible open-source project for recommendation systems. It incorporates diverse AI models like ranking algorithms, sequence recall, multi-interest models, and graph-based techniques. Designed for both beginners and advanced users, it enables rapid construction of efficient, custom recommendation engines.
reczoo/RecBook
推荐系统修炼手册
alimamarankgroup/HPMN
Lifelong sequential modeling for user response prediction. A comprehensive evaluation framework for our SIGIR 2019 paper.
titicaca/spark-gbtlr
Hybrid model of Gradient Boosting Trees and Logistic Regression (GBDT+LR) on Spark
CRIPAC-DIG/Fi_GNN
[CIKM 2019] Code and dataset for "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction"
loserChen/Awesome-Recommender-System
The collection of papers about recommender system
Lapis-Hong/Wide-ResDNN
Wide and Deep Learning(Wide&ResDNN) for Kaggle Criteo Dataset in tensorflow
StrayCamel247/Django_web
✨ DJANGO3.1 网站，集成用户管理，文章博客管理，算法模型可视化系统等功能
fanoping/DIN-pytorch
PyTorch Implementation of Deep Interest Network for Click-Through Rate Prediction
Fisher87/ai_explore
机器学习、深度学习基础知识. 推荐系统及nlp相关算法实现