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recommend-system-tf2.0 icon recommend-system-tf2.0

原理解析及代码实战,推荐算法也可以很简单 🔥 想要系统的学习推荐算法的小伙伴,欢迎 Star 或者 Fork 到自己仓库进行学习🚀 有任何疑问欢迎提 Issues,也可加文末的联系方式向我询问!

recommender-system icon recommender-system

A developing recommender system in tensorflow2. Algorithm: UserCF, ItemCF, LFM, SLIM, GMF, MLP, NeuMF, FM, DeepFM, MKR, RippleNet, KGCN and so on.

recsys_faiss icon recsys_faiss

一个基于 fasttext + faiss 的商品内容相关推荐实现,nginx+uwsgi+flask / gunicorn+uvicorn+fastapi 提供api查询接口,增加Spark实现 Ansj+Word2vec+LSH+Phoenix

rsdeepmodel icon rsdeepmodel

【最新版】深度学习模型(推荐场景CTR预估为背景), 使用estimator进行封装, 包括dnn、deepfm、din、dinfm、autoint等模型

rspapers icon rspapers

A Curated List of Must-read Papers on Recommender System.

silvensnrecsys icon silvensnrecsys

Primary Recommender System: online[matching|ranking...](Flask|Vue) - nearline[model serving|real-time service](Flink|tensorflow serving|redis) - offline[feature engine|model training](Spark|Hdfs(Hbase)|tf)

team-learning-rs icon team-learning-rs

主要存储Datawhale组队学习中“推荐系统”方向的资料。

tensorflow_serving_examples icon tensorflow_serving_examples

利用tensorflow/serving进行单模型、多模型、同一模型多版本的部署,并进行模型预测,并用Prothemus进行服务监控。

tf-ncf icon tf-ncf

A Neural Collaborative Filtering implementation with tensorflow estimator.

tr_linucb icon tr_linucb

Code for the paper "Truncated LinUCB for Stochastic Linear Bandits"

wide_deep icon wide_deep

Wide and Deep Learning for CTR Prediction in tensorflow

xgboost-serving icon xgboost-serving

A flexible, high-performance serving system for machine learning models

zhihu icon zhihu

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

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