Reusable deep learning models for recommendation systems
-
Updated
Aug 20, 2020 - Python
Reusable deep learning models for recommendation systems
Explicit high order interaction models implemented in Keras, including: DCN, xDeepFM, AutoInt etc.
AlitaNet: A click through rate (ctr) prediction deep learning Network implementation with TensorFlow, including LR, FM, AFM, Wide&Deep, DeepFM, xDeepFM, AutoInt, FiBiNet, LS-PLM, DCN, etc.
A easy library for recommendation system or computational advertising
rater, recommender systems. 推荐模型,包括:DeepFM,Wide&Deep,DIN,DeepWalk,Node2Vec等模型实现,开箱即用。
some ctr model, implemented by PyTorch, such as Factorization Machines, Field-aware Factorization Machines, DeepFM, xDeepFM, Deep Interest Network
LightCTR is a tensorflow 2.0 based, extensible toolbox for building CTR/CVR predicting models.
主流推荐系统Rank算法的实现
CTR模型代码和学习笔记总结
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。
DeepTables: Deep-learning Toolkit for Tabular data
CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)
Factorization Machine models in PyTorch
Recommender Learning with Tensorflow2.x
Add a description, image, and links to the xdeepfm topic page so that developers can more easily learn about it.
To associate your repository with the xdeepfm topic, visit your repo's landing page and select "manage topics."