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maikeke's Projects

2016ccf_bdci_sougou icon 2016ccf_bdci_sougou

【源码以及PPT分享】2016CCF大数据与计算智能大赛：精准营销中搜狗用户画像挖掘

awesome-java icon awesome-java

Collection of awesome Java project on Github(非常棒的 Java 开源项目集合).

bigdata icon bigdata

BigData Project 大数据项目由浅入深

convmf icon convmf

卷积神经网络（CNN）提取影评特征构建电影推荐系统，pytorch实现

deeplearning_scala icon deeplearning_scala

scala实现的深度学习deeplearning，包括da，rbm，sda，dbn，cnn，rnn

eshop icon eshop

电商+大数据+spark机器学习

estuary icon estuary

A toy Deep Learning framework in Scala.

flink-recommandsystem-demo icon flink-recommandsystem-demo

:helicopter::rocket:基于Flink实现的商品实时推荐系统。flink统计商品热度，放入redis缓存，分析日志信息，将画像标签和实时记录放入Hbase。在用户发起推荐请求后，根据用户画像重排序热度榜，并结合协同过滤和标签两个推荐模块为新生成的榜单的每一个产品添加关联产品，最后返回新的用户列表。

jstarcraft-rns icon jstarcraft-rns

专注于解决推荐领域与搜索领域的两个核心问题:排序预测(Ranking)和评分预测(Rating). 为相关领域的研发人员提供完整的通用设计与参考实现. 涵盖了70多种排序预测与评分预测算法,是最快最全的Java推荐与搜索引擎.

mmlspark icon mmlspark

Microsoft Machine Learning for Apache Spark

movie_recommender icon movie_recommender

MovieLens based recommender system.使用MovieLens数据集训练的电影推荐系统。

product-recommendation-system icon product-recommendation-system

:sunrise: 基于用户的协同过滤算法实现的商品推荐系统 https://github.com/MrQuJL/product-recommendation-system

recommend icon recommend

Python 3.6 下的推荐算法解析，尽量使用简单的语言剖析原理，相似度度量、协同过滤、矩阵分解等

recommondation-system icon recommondation-system

一些传统推荐算法的实现，包括基于内容的推荐，协同过滤，矩阵分解

redis icon redis

Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes

rl4j icon rl4j

Deep Reinforcement Learning for the JVM (Deep-Q, A3C)

spark icon spark

Apache Spark - A unified analytics engine for large-scale data processing

spark_als icon spark_als

基于spark-ml,spark-mllib,spark-streaming的推荐算法实现

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