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