crr121 Goto Github PK

movielens-recsys

基于MovieLens-1M数据集实现的协同过滤算法demo

movielens_recommender

Recommendation algorithms based on MovieLens

msjava

【Java后端核心知识体系】-记录学习过程_保持持续学习的好习惯

myresume

Latex template of my resume

nettystudy

IO与Netty的学习

notes

Java后台-基础知识点整理

notes-for-loop-questions

斐波那契数列，鸡兔同笼，十进制和二进制转换，质数判断与循环输出，奇数之和

opencv

oracle

os_course_info

os course info

pdf

编程电子书，电子书，编程书籍，包括C，C#，Docker，Elasticsearch，Git，Hadoop，HeadFirst，Java，Javascript，jvm，Kafka，Linux，Maven，MongoDB，MyBatis，MySQL，Netty，Nginx，Python，RabbitMQ，Redis，Scala，Solr，Spark，Spring，SpringBoot，SpringCloud，TCPIP，Tomcat，Zookeeper，人工智能，大数据类，并发编程，数据库类，数据挖掘，新面试题，架构设计，算法系列，计算机类，设计模式，软件测试，重构优化，等更多分类

randomnum

recommendation

Implementation of SVD and SVD++ for recommendation

recommender-system

利用MovieLens数据，Pearson相似度，分别基于User和Item构建一个简单的kNN推荐系统，并给出RMSE评测

recommender-system-1

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

recommender-systems

Information Retrieval course. Basic baseline, KNN, Matrix factoriztion. Using SGD.

recommendersystem-dataset

This repository contains some datasets that I have collected in Recommender Systems.

recsys-1

计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估

recsys2019_deeplearning_evaluation

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

redis

《Redis Command Reference》全文的中文翻译版。

resume

An elegant \LaTeX\ résumé template

resumecls

A LaTeX cls to typeset resume both in English and Chinese

rspapers

Must-read papers on Recommender System.

selectionsort

java选择排序

sgd-pmf

SGD for Probabilistic Matrix Factorization(PMF)

simplewebserver

SimpleWebServer 是一款使用Java基于NIO编写的超轻量级开源Web Application Server

studentmanagesystem

surprise

A Python scikit for building and analyzing recommender systems

svdrecommendersystem

将SVD应用于推荐系统中的评分预测问题

tesnsorflow-introduction