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‎docs/_sidebar.md‎

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- 目录
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- 第一章 推荐系统概述
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- [1.1 推荐系统的意义](/ch01/ch1.1)
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- [1.2 推荐系统架构](ch01/ch1.2)
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- [1.3 推荐系统技术栈](ch01/ch1.3)
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- [1.2 推荐系统架构](/ch01/ch1.2)
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- [1.3 推荐系统技术栈](/ch01/ch1.3)
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- 第二章 推荐系统算法基础
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- 2.1 经典召回模型
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- 2.1.1 基于协同过滤的召回
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- [UserCF](ch02/ch2.1/ch2.1.1/usercf)
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- [ItemCF](ch02/ch2.1/ch2.1.1/itemcf)
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- [Swing](ch02/ch2.1/ch2.1.1/Swing)
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- [矩阵分解](ch02/ch2.1/ch2.1.1/mf)
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- [UserCF](/ch02/ch2.1/ch2.1.1/usercf)
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- [ItemCF](/ch02/ch2.1/ch2.1.1/itemcf)
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- [Swing](/ch02/ch2.1/ch2.1.1/Swing)
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- [矩阵分解](/ch02/ch2.1/ch2.1.1/mf)
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- 2.1.2 基于向量的召回
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- [FM召回](ch02/ch2.1/ch2.1.2/FM)
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- [FM召回](/ch02/ch2.1/ch2.1.2/FM)
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- item2vec召回系列
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- [word2vec原理](ch02/ch2.1/ch2.1.2/word2vec)
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- [item2vec召回](ch02/ch2.1/ch2.1.2/item2vec)
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- [Airbnb召回](ch02/ch2.1/ch2.1.2/Airbnb)
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- [YoutubeDNN召回](ch02/ch2.1/ch2.1.2/YoutubeDNN)
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- [word2vec原理](/ch02/ch2.1/ch2.1.2/word2vec)
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- [item2vec召回](/ch02/ch2.1/ch2.1.2/item2vec)
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- [Airbnb召回](/ch02/ch2.1/ch2.1.2/Airbnb)
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- [YoutubeDNN召回](/ch02/ch2.1/ch2.1.2/YoutubeDNN)
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- 双塔召回
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- [经典双塔](ch02/ch2.1/ch2.1.2/DSSM)
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- [Youtube双塔](ch02/ch2.1/ch2.1.2/YoutubeTwoTower)
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- [经典双塔](/ch02/ch2.1/ch2.1.2/DSSM)
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- [Youtube双塔](/ch02/ch2.1/ch2.1.2/YoutubeTwoTower)
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- 2.1.3 基于图的召回
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- [EGES](ch02/ch2.1/ch2.1.3/EGES)
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- [PinSAGE](ch02/ch2.1/ch2.1.3/PinSage)
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- [EGES](/ch02/ch2.1/ch2.1.3/EGES)
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- [PinSAGE](/ch02/ch2.1/ch2.1.3/PinSage)
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- 2.1.4 基于序列的召回
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- [MIND](ch02/ch2.1/ch2.1.4/MIND)
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- [SDM](ch02/ch2.1/ch2.1.4/SDM)
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- [MIND](/ch02/ch2.1/ch2.1.4/MIND)
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- [SDM](/ch02/ch2.1/ch2.1.4/SDM)
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- 2.1.5 基于树模型的召回
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- [TDM](ch02/ch2.1/ch2.1.5/TDM)
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- [TDM](/ch02/ch2.1/ch2.1.5/TDM)
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- 2.2 经典排序模型
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- [2.2.1 GBDT+LR](ch02/ch2.2/ch2.2.1)
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- [2.2.1 GBDT+LR](/ch02/ch2.2/ch2.2.1)
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- 2.2.2 特征交叉
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- [FM](ch02/ch2.2/ch2.2.2/FM)
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- [PNN](ch02/ch2.2/ch2.2.2/PNN)
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- [DCN](ch02/ch2.2/ch2.2.2/DCN)
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- [AutoInt](ch02/ch2.2/ch2.2.2/AutoInt)
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- [FiBiNet](ch02/ch2.2/ch2.2.2/FiBiNet)
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- [FM](/ch02/ch2.2/ch2.2.2/FM)
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- [PNN](/ch02/ch2.2/ch2.2.2/PNN)
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- [DCN](/ch02/ch2.2/ch2.2.2/DCN)
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- [AutoInt](/ch02/ch2.2/ch2.2.2/AutoInt)
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- [FiBiNet](/ch02/ch2.2/ch2.2.2/FiBiNet)
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- 2.2.3 Wide&Deep系列
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- [Wide&Deep](ch02/ch2.2/ch2.2.3/WideNDeep)
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- [NFM](ch02/ch2.2/ch2.2.3/NFM)
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- [AFM](ch02/ch2.2/ch2.2.3/AFM)
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- [DeepFM](ch02/ch2.2/ch2.2.3/DeepFM)
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- [xDeepFM](ch02/ch2.2/ch2.2.3/xDeepFM)
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- [Wide&Deep](/ch02/ch2.2/ch2.2.3/WideNDeep)
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- [NFM](/ch02/ch2.2/ch2.2.3/NFM)
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- [AFM](/ch02/ch2.2/ch2.2.3/AFM)
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- [DeepFM](/ch02/ch2.2/ch2.2.3/DeepFM)
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- [xDeepFM](/ch02/ch2.2/ch2.2.3/xDeepFM)
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- 2.2.4 序列模型
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- [DIN](ch02/ch2.2/ch2.2.4/DIN)
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- [DIEN](ch02/ch2.2/ch2.2.4/DIEN)
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- [DSIN](ch02/ch2.2/ch2.2.4/DSIN)
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- [DIN](/ch02/ch2.2/ch2.2.4/DIN)
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- [DIEN](/ch02/ch2.2/ch2.2.4/DIEN)
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- [DSIN](/ch02/ch2.2/ch2.2.4/DSIN)
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- 2.2.5 多任务学习
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- [多任务学习概述](ch02/ch2.2/ch2.2.5/2.2.5.0)
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- [ESMM](ch02/ch2.2/ch2.2.5/ESMM)
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- [MMOE](ch02/ch2.2/ch2.2.5/MMOE)
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- [PLE](ch02/ch2.2/ch2.2.5/PLE)
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- [多任务学习概述](/ch02/ch2.2/ch2.2.5/2.2.5.0)
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- [ESMM](/ch02/ch2.2/ch2.2.5/ESMM)
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- [MMOE](/ch02/ch2.2/ch2.2.5/MMOE)
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- [PLE](/ch02/ch2.2/ch2.2.5/PLE)
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- 第三章 推荐系统实战
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- 3.1 天池入门赛-新闻推荐
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- [3.1.1 赛题理解&Baseline](ch03/ch3.1/markdown/ch3.1.1)
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- [3.1.2 数据分析](ch03/ch3.1/markdown/ch3.1.2)
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- [3.1.3 多路召回](ch03/ch3.1/markdown/ch3.1.3)
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- [3.1.4 特征工程](ch03/ch3.1/markdown/ch3.1.4)
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- [3.1.5 排序模型&模型融合](ch03/ch3.1/markdown/ch3.1.5)
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- [3.1.1 赛题理解&Baseline](/ch03/ch3.1/markdown/ch3.1.1)
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- [3.1.2 数据分析](/ch03/ch3.1/markdown/ch3.1.2)
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- [3.1.3 多路召回](/ch03/ch3.1/markdown/ch3.1.3)
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- [3.1.4 特征工程](/ch03/ch3.1/markdown/ch3.1.4)
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- [3.1.5 排序模型&模型融合](/ch03/ch3.1/markdown/ch3.1.5)
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- 3.2 新闻推荐系统的实践
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- [3.2.1 特别说明(必看)](ch03/ch3.2/3.2)
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- [3.2.1 特别说明(必看)](/ch03/ch3.2/3.2)
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- 3.2.1 离线物料系统的构建
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- [Mysql](ch03/ch3.2/3.2.1.1)
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- [MongoDB](ch03/ch3.2/3.2.1.2)
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- [Redis](ch03/ch3.2/3.2.1.3)
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- [Scrapy](ch03/ch3.2/3.2.1.4)
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- [自动化构建用户及物料画像](ch03/ch3.2/3.2.1.5)
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- [Mysql](/ch03/ch3.2/3.2.1.1)
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- [MongoDB](/ch03/ch3.2/3.2.1.2)
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- [Redis](/ch03/ch3.2/3.2.1.3)
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- [Scrapy](/ch03/ch3.2/3.2.1.4)
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- [自动化构建用户及物料画像](/ch03/ch3.2/3.2.1.5)
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- 3.2.2 前后端基础及交互
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- [前端基础及Vue实战](ch03/ch3.2/3.2.2.1)
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- [flask简介及基础](ch03/ch3.2/3.2.2.2)
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- [前后端交互](ch03/ch3.2/3.2.2.3)
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- [3.2.3 推荐系统流程的构建](ch03/ch3.2/3.2.3)
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- [前端基础及Vue实战](/ch03/ch3.2/3.2.2.1)
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- [flask简介及基础](/ch03/ch3.2/3.2.2.2)
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- [前后端交互](/ch03/ch3.2/3.2.2.3)
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- [3.2.3 推荐系统流程的构建](/ch03/ch3.2/3.2.3)
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- 3.2.4 召回
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- [规则类召回](ch03/ch3.2/3.2.4.1)
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- [YouTubeDNN召回](ch03/ch3.2/3.2.4.2)
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- [DSSM召回](ch03/ch3.2/3.2.4.3)
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- [3.2.5 DeepFM排序](ch03/ch3.2/3.2.5)
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- [3.2.6 重排(打散策略)](ch03/ch3.2/3.2.6)
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- [规则类召回](/ch03/ch3.2/3.2.4.1)
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- [YouTubeDNN召回](/ch03/ch3.2/3.2.4.2)
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- [DSSM召回](/ch03/ch3.2/3.2.4.3)
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- [3.2.5 DeepFM排序](/ch03/ch3.2/3.2.5)
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- [3.2.6 重排(打散策略)](/ch03/ch3.2/3.2.6)
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- 3.2.8 当前问题汇总
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- [熟悉推荐系统基本流程问答整理](ch03/ch3.2/3.2.8.1)
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- [数据库的基本使用问答整理](ch03/ch3.2/3.2.8.2)
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- [离线物料系统的构建问答整理](ch03/ch3.2/3.2.8.3)
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- [熟悉推荐系统基本流程问答整理](/ch03/ch3.2/3.2.8.1)
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- [数据库的基本使用问答整理](/ch03/ch3.2/3.2.8.2)
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- [离线物料系统的构建问答整理](/ch03/ch3.2/3.2.8.3)
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- 第四章 推荐系统算法面经
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- [4.1 ML与DL基础](ch04/ch4.1)
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- [4.2 推荐模型相关](ch04/ch4.2)
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- [4.3 热门技术相关](ch04/ch4.3)
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- [4.4 业务场景相关](ch04/ch4.4)
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- [4.5 HR及其他](ch04/ch4.5)
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- [4.1 ML与DL基础](/ch04/ch4.1)
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- [4.2 推荐模型相关](/ch04/ch4.2)
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- [4.3 热门技术相关](/ch04/ch4.3)
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- [4.4 业务场景相关](/ch04/ch4.4)
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- [4.5 HR及其他](/ch04/ch4.5)

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