视频齐全,缺文档目录已红字标出

├─第1章 课程介绍与学习指南
│&nBSp; &nBSp;&nBSp; &nBSp;1-1 课程介绍及导学.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第2章 了解推荐系统的生态
│&nBSp; &nBSp;&nBSp; &nBSp;[图文]2-1 本章重难点提点[缺]
│&nBSp; &nBSp;&nBSp; &nBSp;2-2 推荐系统的关键元素和思维模式.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;2-3 推荐算法的主要分类.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;2-4 推荐系统常见的问题.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;2-5 推荐系统效果评测.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第3章 给学习算法打基础
│&nBSp; &nBSp;&nBSp; &nBSp;图文：3-1 本章重点难点提点[缺]
│&nBSp; &nBSp;&nBSp; &nBSp;3-2 推荐系统涉及的数学知识.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;3-3 推荐系统涉及的概率统计知识.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第4章 详解协同过滤推荐算法原理
│&nBSp; &nBSp;&nBSp; &nBSp;图文：4-1 本章重点难点提点[缺]
│&nBSp; &nBSp;&nBSp; &nBSp;4-2 本章作业.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-3 协同过滤的数学知识：最小二乘法.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-4 协同过滤的数学知识：梯度下降法.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-5 协同过滤的数学知识：余弦相似度.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-6 什么是user-based的协同过滤.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-7 基于Spark实现user-based协同过滤.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-8 什么是item-based协同过滤.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-9 基于Spark实现item-based协同过滤.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-10 基于模型的协同过滤.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-11 基于矩阵分解模型的两种算法：SVD和PMF.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;4-12 缺失值填充.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第5章 Spark内置推荐算法ALS原理
│&nBSp; &nBSp;&nBSp; &nBSp;5-1 ALS 算法原理.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;5-2 ALS 算法在Spark上的实现.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;5-3 ALS 算法在 Spark 上的源码分析.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第6章 推荐系统搭建——需求分析和环境搭建
│&nBSp; &nBSp;&nBSp; &nBSp;图文：6-1 本章重点难点提点[缺]
│&nBSp; &nBSp;&nBSp; &nBSp;6-2 项目需求分析 技术分解 模块设计.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;6-3 开发环境搭建.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;6-4 环境问题 工具问题 版本问题.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第7章 推荐系统搭建——UI界面模块
│&nBSp; &nBSp;&nBSp; &nBSp;7-1 Vue+ElementUI简单入门.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;7-2 用户访问页面实现.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;7-3 AB Test 控制台页面（上）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;7-4 AB Test 控制台页面（下）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第8章 推荐系统搭建——数据层
│&nBSp; &nBSp;&nBSp; &nBSp;8-1 数据上报（上）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;8-2 数据上报（下）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;8-3 日志清洗和格式化数据（上）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;8-4 日志清洗和格式化数据（中）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;8-5 日志清洗和格式化数据（下）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;8-6 分析用户行为和商品属性.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第9章 推荐系统搭建——推荐引擎
│&nBSp; &nBSp;&nBSp; &nBSp;9-1 基于用户行为构建评分矩阵.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-2 离线推荐：基于用户角度召回策略筛选候选集（上）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-3 离线推荐：基于用户角度召回策略筛选候选集（下）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-4 离线推荐：基于物品角度召回策略筛选候选集（上）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-5 离线推荐：基于物品角度召回策略筛选候选集（下）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-6 离线推荐：写特征向量到HBase.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-7 离线推荐：基于模型的排序.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-8 实时推荐：Storm解析用户行为.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-9 实时推荐：通过FTRL更新特征权重-原理.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-10 实时推荐：通过FTRL更新特征权重-代码实现.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;9-11 离线推荐和实时推荐项目梳理.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第10章 推荐系统搭建——推荐结果存储
│&nBSp; &nBSp;&nBSp; &nBSp;10-1 数仓ODS和DWD层搭建.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;10-2 搭建用户行为日志数据仓库.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;10-3 利用外部分区表存储用户行为.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第11章 推荐系统搭建——推荐效果评估模块
│&nBSp; &nBSp;&nBSp; &nBSp;11-1 AB Test.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;11-2 AB Test的分流管理.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;11-3 搭建AB Test 实验控制台（上）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;11-4 搭建AB Test 实验控制台（下）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;11-5 常用评测指标.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第12章 知识拓展——基于关联规则的推荐算法
│&nBSp; &nBSp;&nBSp; &nBSp;12-1 基于APriori的关联算法.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;12-2 基于Spark实现APriori算法（上）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;12-3 基于Spark实现APriori算法（下）.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;12-4 基于FP-Growth的关联算法.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;12-5 基于Spark实现FP-Growth算法.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第13章 知识拓展——基于机器学习的推荐算法
│&nBSp; &nBSp;&nBSp; &nBSp;13-1 RBM神经网络.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;13-2 CNN卷积神经网络.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;13-3 RNN循环神经网络.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
├─第14章 知识拓展——基于内容的推荐算法
│&nBSp; &nBSp;&nBSp; &nBSp;14-1 文本向量化.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;14-2 基于Spark实现TF-IDF.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;14-3 课程总结.mp4
│&nBSp; &nBSp;&nBSp; &nBSp;
└─课程资料
&nBSp; &nBSp;&nBSp; &nBSp;&nBSp;&nBSp;代码.zIP

*声明：课程资源购自网络，版权归原作者所有，仅供参考学习使用，严禁外传及商用，若侵犯到您的权益请联系客服删除。