文件内容:
file:06.07_推荐系统冷启动问题.mp4
file:08.06_MLlib推荐实例之探索DataFrame_实践.mp4
file:04.01_什么是lambda架构.mp4
file:05.03_用户画像系统流程.mp4
file:05.14_代码示例4之模型调优-实践【整理不易‖免费奉上：cunlove.cn】.mp4
file:08.01_Mahout推荐实战补充-实践.mp4
file:01.01_大数据应用案例【持续更新‖免费提供：cunlove.cn】.mp4
file:05.12_代码实例3之模型调优.mp4
file:09.02_推荐系统数据收集背景.mp4
file:06.04_相似度的计算.mp4
file:07.15_Mahout推荐实例7之图书推荐3-实践.mp4
file:08.05_MLlib推荐实例之定义解析函数-实践【手动整理‖免费开放：cunlove.cn】.mp4
file:09.04_Web日志数据采集Flume部署配置-实践.mp4
file:07.03_Mahout推荐系统评估.mp4
file:06.08_推荐案例实践准备.mp4
file:06.03_基于协同过滤的推荐算法.mp4
file:08.09_推荐实战之开发环境准备-实践【持续更新‖免费提供：cunlove.cn】.mp4
file:02.01_什么是推荐系统（处理）【耗时整理‖免费分享：cunlove.cn】.mp4
file:04.03_Lambda架构之实时处理层.mp4
file:08.03_MLlib推荐算法介绍【花费时间‖免费获取：cunlove.cn】.mp4
file:09.03_FlumeNG数据收集系统.mp4
file:07.16_Mahout推荐系统实战-实践.mp4
file:07.01_Mahout概述【更多精选‖公众号：CunWorkNotes 获取】.mp4
file:05.08_代码实例1之模型训练及参数设置-实践.mp4
file:07.08_Mahout推荐实例4之模型评估1-实践【良心整理‖免费获取：cunlove.cn】.mp4
file:05.09_代码实例1之参数设置及模型测试-实践【不易整理‖请关注：CunWorkNotes】.mp4
file:09.13_推荐系统离线层实现-实践.mp4
file:06.01_推荐模型构建流程.mp4
file:06.05_基于模型的方法.mp4
file:05.06_算法和模型的评价.mp4
folder:121623_spark大数据互联网项目实战推荐系统（全套）