搜索资源列表
CollectiveIntelligence
- CollectiveIntelligence,集体智慧与推荐系统,数据挖掘类图书-CollectiveIntelligence, the collective wisdom and recommendation systems, data mining books
A
- movie lense的用户推荐数据,用于用户推荐系统的仿真与研究-movie lense user recommendation data, the user recommendation system for simulation and study
project
- 数据挖掘,推荐系统,堆叠降噪自编码器,逻辑回归(Data mining, recommender systems, stack noise reduction, self coder, logic regression)
DpRecommendations
- 一个带有隐私保护的推荐系统,采用movielens数据集,Topn推荐算法(A recommendation system with privacy protection)
recommend
- 一个关于自己实现推荐系统的案例,搞清楚推荐系统的实现过程(A recommendation on the implementation of their own system, clear the recommendation system to achieve the process)
python-recsys-master
- 《推荐系统实践》作者:项亮;书籍全部章节配套源代码;仅供学习分享,如有侵权立刻删除。(The "source code" of Recommended system practice.)
machine-learning-ex8
- Andrew Ng Cousera 机器学习 异常检测勇于服务器故障分析以及用于电影推荐的推荐系统的源代码和说明文档。(Andrew Ng Cousera's machine learning implement the anomaly detection algorithm and apply it to detect failing servers on a network. In the second part, you will use collaborative filtering t
cross-filter
- 电影推荐系统,运用协同过滤算法,运行ex8_cofi进入主程序(The application of collaborative filtering algorithm in movie recommendation system)
推荐系统实践
- 《推荐系统实践》超高清电子书,带书签,完整版。("Practice of recommending system" ultra high definition electronic books, with bookmarks.)
recommendationsystem
- web大数据的推荐系统,课堂留的作业,参考(recommend system, the big homework about web)
recommender
- 利用scala实现的推荐系统,其中用到了hive、kafka、scala等(A recommendation system implemented using Scala, which uses hive, Kafka, Scala and so on)
股票推荐系统
- 基于股票推荐系统 硬件环境 CPU:Pentium III 800MHz的 (最好是Intel Pentium IV 1GMHz) 内存:512MB(最好是1GB) 硬盘:至少6GB 2)软件环境 操作系统:Windows 2003 Server 数据库:SQL Server 2005 编程环境:Matlab R2009a,MicroSoft Visual Basic 6.0(stock recsystem hardware CPU: Pentium III 800MHz
code
- 协同过滤算法,用python编写,可用于推荐系统中的协同过滤推荐算法。文件包含mariadb数据库数据导入,数据预处理等代码。(Collaborative filtering algorithm, written in Python)
MovieLens-RecSys-master
- “推荐系统实践”,项亮,代码。数据“下载Movielens 1M数据集[ml-1m.zip](http://files.grouplens.org/datasets/movielens/ml-1m.zip),并解压到项目MovieLens-RecSys文件夹下”("Recommending system practice", light, code. The data "downloads the Movielens 1M data set [ml-1m.zip]
基于协同过滤算法的电影推荐系统
- 基于协调过滤算法的电影推荐系统Java实现代码(Java implementation code of movie recommendation system based on coordinated filtering algorithm)
CollaborativeFiltering-master
- 协同过滤算法的实现,基于协同过滤算法的推荐系统,在电子商务领域有着极为广泛的应用。(Collaborative Filtering)
YuanNews-master
- 使用java web实现的推荐系统网页 分为用户层和管理层 管理层可以从后台看到用户和新闻的所有信息(Web pages of recommendation system implemented by java web are divided into user layer and management layer. All information of users and news can be seen from the background.)
智能推荐系统
- python关于智能推荐系统的小案例,有利于初学者学习的项目与入门(Python's small case about intelligent recommendation system is helpful for beginners to learn project and introduction)
电影推荐系统
- 电影推荐系统,是用python在tensorflow的环境下具体实现的(Movie recommendation system is implemented by Python in tensorflow environment)
电影推荐算法
- 电影推荐系统代码,使用了迭代SVD算法,其实是老师布置的期末作业,正确性已由老师验证(Movie recommendation system code)