#计算机科学#Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
翻译 - 基于深度学习的CTR模型的易于使用，模块化和可扩展的软件包。
Tensorflow implementation of DeepFM for CTR prediction.
#计算机科学#Code for the IJCAI'19 paper "Deep Session Interest Network for Click-Through Rate Prediction"
ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embeddin...
LightCTR is a tensorflow 2.0 based, extensible toolbox for building CTR/CVR predicting models.
PyTorch Implementation of Deep Interest Network for Click-Through Rate Prediction
#计算机科学#some ctr model, implemented by PyTorch, such as Factorization Machines, Field-aware Factorization Machines, DeepFM, xDeepFM, Deep Interest Network
The source code of MacGNN, The Web Conference 2024.
Dataset and code for “Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction”
Click-Through Rate Estimation for Rare Events in Online Advertising
A curated list of papers on click-through-rate (CTR) prediction.
#计算机科学#In this project I used ML modeling and data analysis to predict ad clicks and significantly improve ad campaign performance, resulting in a 43.3% increase in profits. The selected model was Logistic R...
The source code of NRCGI (Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction, CIKM2023).
This is an official implementation of feature interaction for BaGFN
Here I demonstrate the performance difference between the Poisson and the classic bootstrap by estimating the confidence interval for the difference of CTRs of the two user groups
The Most Complete PyTorch Implementation of "Deep Interest Network for Click-Through Rate Prediction"
Training pipeline using TFRecord files
StrikePrick is your one-stop destination for exposing and overturning ineffective, outdated email marketing strategies. This repository offers a data-driven, humor-infused critique of commonly touted ...