Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

Recommender Learning with Tensorflow2.x

Factorization Machine models in PyTorch

Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" (RecSys2020)

练习下用pytorch来复现下经典的推荐系统模型, 如MF, FM, DeepConn, MMOE, PLE, DeepFM, NFM, DCN, AFM, AutoInt, ONN, FiBiNET, DCN-v2, AFN, DCAP等

CTR模型代码和学习笔记总结

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

主流推荐系统Rank算法的实现

基于 Pytorch 实现推荐系统相关的算法

LightCTR is a tensorflow 2.0 based, extensible toolbox for building CTR/CVR predicting models.

Here are the models listed in CTR. Example: FM、DeepFM、xDeepFM etc.

A pytorch implementation for He et al. Neural Factorization Machines for Sparse Predictive Analytics on SIGIR 2017.

Implementation with Pytorch of DeepCrossing, DeepFM,NFM,Wide&Deep

一些CTR模型和常见特征工程的方法

A easy library for recommendation system or computational advertising

TOMMY is een topic modelling applicatie die ontwikkeld is door studenten van de Universiteit Utrecht in opdracht van EMMA. Voor het uitvoeren van topic modelling wordt het achterliggende Latent Dirichlet Allocation (LDA) algoritme of Non-Negative Matrix Factorization (NMF) algoritme uitgevoerd op de door de gebruiker aangeleverde bestanden.

Several wines are analyzed in order to gain insights on what features affect a wine's rating using logistic regressions models, kNN algorithms, topic modeling, LDA, and Gensim models.

In this repository, I use the SKLearn library to do topic modeling.

Yet another FM demodulator as a way for me to spend (i.e. waste) my spare time playing with different ways to learn DSP.

This Repo contains all NFM SmartContracts