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Title: GitHub - clown-developer/RecSys: 计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估 · GitHub

Open Graph Title: GitHub - clown-developer/RecSys: 计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估

X Title: GitHub - clown-developer/RecSys: 计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估

Description: 计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估 - clown-developer/RecSys

Open Graph Description: 计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估 - clown-developer/RecSys

X Description: 计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估 - clown-developer/RecSys

Opengraph URL: https://github.com/clown-developer/RecSys

X: @github

direct link

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https://github.com/clown-developer/RecSys#推荐系统计算广告机器学习ctr预估资料汇总
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精选文章https://github.com/mJackie/RecNews
https://github.com/clown-developer/RecSys#roadmap
推荐系统https://github.com/clown-developer/RecSys#%E6%8E%A8%E8%8D%90%E7%B3%BB%E7%BB%9F
计算广告https://github.com/clown-developer/RecSys#%E8%AE%A1%E7%AE%97%E5%B9%BF%E5%91%8A
统计学习模型https://github.com/clown-developer/RecSys#%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%A8%A1%E5%9E%8B
技术文章https://github.com/clown-developer/RecSys#%E6%8A%80%E6%9C%AF%E6%96%87%E7%AB%A0
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深度学习模型https://github.com/clown-developer/RecSys#%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E6%A8%A1%E5%9E%8B
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Criteo Display Advertising Challengehttps://github.com/clown-developer/RecSys#CriteoDisplayAdvertisingChallenge
Avazu Click Through Rate Predictionhttps://github.com/clown-developer/RecSys#AvazuClickThroughRatePrediction
2018 IJCAI 阿里妈妈搜索广告转化预测https://github.com/clown-developer/RecSys#2018-IJCAI-%E9%98%BF%E9%87%8C%E5%A6%88%E5%A6%88%E6%90%9C%E7%B4%A2%E5%B9%BF%E5%91%8A%E8%BD%AC%E5%8C%96%E9%A2%84%E6%B5%8B
2018腾讯广告算法大赛https://github.com/clown-developer/RecSys#2018%E8%85%BE%E8%AE%AF%E5%B9%BF%E5%91%8A%E7%AE%97%E6%B3%95%E5%A4%A7%E8%B5%9B
技术博客https://github.com/clown-developer/RecSys#%E6%8A%80%E6%9C%AF%E5%8D%9A%E5%AE%A2
经典论文清单https://github.com/clown-developer/RecSys#%E7%BB%8F%E5%85%B8%E8%AE%BA%E6%96%87%E6%B8%85%E5%8D%95
https://github.com/clown-developer/RecSys#推荐系统
推荐系统简明教程-概述https://zhuanlan.zhihu.com/p/87411668
推荐系统简明教程-召回https://zhuanlan.zhihu.com/p/87578318
推荐系统简明教程-排序https://zhuanlan.zhihu.com/p/87796986
推荐系统实践-项亮https://github.com/clown-developer/RecSys/blob/master/resource/%E6%8E%A8%E8%8D%90%E7%B3%BB%E7%BB%9F%E5%AE%9E%E8%B7%B5-%E9%A1%B9%E4%BA%AE.pdf
https://github.com/clown-developer/RecSys#计算广告
互联网广告系统综述系列博文https://blog.csdn.net/mytestmy/article/list
计算广告学系列视屏-刘鹏https://study.163.com/course/introduction.htm?courseId=321007#/courseDetail?tab=1
计算广告学讲义-刘鹏https://dirtysalt.github.io/html/computational-advertising.html
https://github.com/clown-developer/RecSys#统计学习模型
https://github.com/clown-developer/RecSys#技术文章
前深度学习时代CTR预估模型的演化之路https://zhuanlan.zhihu.com/p/61154299
逻辑回归LR模型简介https://tech.meituan.com/2015/05/08/intro-to-logistic-regression.html
FFM讲解PPThttps://github.com/clown-developer/RecSys/blob/master/resource/ffm.pdf
深入FFM原理与实践https://tech.meituan.com/2016/03/03/deep-understanding-of-ffm-principles-and-practices.html
GBDT算法原理与系统设计简介https://github.com/clown-developer/RecSys/blob/master/resource/GBDT-wepon.pdf
https://github.com/clown-developer/RecSys#实践工具
LightGBMhttps://github.com/Microsoft/LightGBM
XGBoosthttps://github.com/dmlc/xgboost
LIBFFMhttps://github.com/guestwalk/libffm
xLearnhttps://github.com/aksnzhy/xlearn
DeepCTRhttps://github.com/shenweichen/DeepCTR
https://github.com/clown-developer/RecSys#深度学习模型
https://github.com/clown-developer/RecSys#技术文章-1
深度学习如何应用在广告、推荐及搜索业务？https://mp.weixin.qq.com/s/nboZ6p_l30L__FJNyz6Ohw
深度学习在CTR预估中的应用https://zhuanlan.zhihu.com/p/35484389
深度学习在 CTR 中应用http://www.mamicode.com/info-detail-1990002.html
深度学习在美团点评推荐业务中实践https://gitbook.cn/books/5aa0dd15cfbe2c144b71906d/index.html
https://github.com/clown-developer/RecSys#实践代码
CTR预估算法之FM, FFM, DeepFM及实践https://github.com/Johnson0722/CTR_Prediction
推荐系统中使用ctr排序的dnn模型https://github.com/nzc/dnn_ctr
https://github.com/clown-developer/RecSys#相关比赛
CriteoDisplayAdvertisingChallengehttps://www.kaggle.com/c/criteo-display-ad-challenge
https://github.com/clown-developer/RecSys#criteodisplayadvertisingchallenge
借鉴了Facebook的方案: GBDT 特征编码 + FFMhttps://www.kaggle.com/c/criteo-display-ad-challenge/discussion/10555
Quadratic Feature Generation + FTRL 传统特征工程和 FTRL 线性模型的结合https://www.kaggle.com/c/criteo-display-ad-challenge/discussion/10534
AvazuClickThroughRatePredictionhttps://www.kaggle.com/c/avazu-ctr-prediction
https://github.com/clown-developer/RecSys#avazuclickthroughrateprediction
Feature Engineering + FFM + Ensemble, 只基于 FFM 进行集成https://www.kaggle.com/c/avazu-ctr-prediction/discussion/12608
Feature Engineering + GBDT 特征编码 + FFM + Blendinghttps://github.com/owenzhang/kaggle-avazu
2018 IJCAI 阿里妈妈搜索广告转化预测https://tianchi.aliyun.com/competition/entrance/231647/introduction?spm=5176.12281957.1004.10.38b04c2aaROEf9
https://github.com/clown-developer/RecSys#2018-ijcai-阿里妈妈搜索广告转化预测
GBDT，用了嫁接技术处理样本分布不一致https://github.com/plantsgo/ijcai-2018
GBDT单模型+大量特征工程https://github.com/YouChouNoBB/ijcai-18-top2-single-mole-solution
2018腾讯广告算法大赛https://algo.qq.com/
https://github.com/clown-developer/RecSys#2018腾讯广告算法大赛
https://github.com/DiligentPanda/Tencent_Ads_Algo_2018https://github.com/DiligentPanda/Tencent_Ads_Algo_2018
https://github.com/nzc/tencent-contesthttps://github.com/nzc/tencent-contest
https://github.com/clown-developer/RecSys#技术博客
深度推荐系统https://zhuanlan.zhihu.com/deep-recsys
美团技术点评https://tech.meituan.com/
深度学习沿言笔记https://zhuanlan.zhihu.com/c_188941548
王喆的机器学习笔记https://zhuanlan.zhihu.com/wangzhenotes
推荐系统理论及实战https://www.jianshu.com/nb/21403842
刘十三的机器学习笔记https://zhuanlan.zhihu.com/c_1169669630389440512
https://github.com/clown-developer/RecSys#经典论文清单
Wide & Deep Learning for Recommender Systemshttps://github.com/clown-developer/RecSys/blob/master/paper/wide&deep.pdf
DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Predictionhttps://github.com/clown-developer/RecSys/blob/master/paper/deepfm.pdf
Practical lessons from predicting clicks on ads at facebookhttps://github.com/clown-developer/RecSys/blob/master/paper/2014GBDT+LR-Facebook.pdf
Deep Neural Networks for YouTube Recommendationshttps://github.com/clown-developer/RecSys/blob/master/paper/youtube-recsys.pdf
Real-time Personalization using Embeddings for Search Ranking at Airbnbhttps://github.com/clown-developer/RecSys/blob/master/paper/airbnb2018KDD.pdf
Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Ratehttps://github.com/clown-developer/RecSys/blob/master/paper/ESSM2018.pdf
Real-time Personalization using Embeddings for Search Ranking at Airbnbhttps://github.com/clown-developer/RecSys/blob/master/paper/aribnbSearch.pdf
搜索引擎点击模型综述https://github.com/clown-developer/RecSys/blob/master/paper/%E6%90%9C%E7%B4%A2%E5%BC%95%E6%93%8E%E7%82%B9%E5%87%BB%E6%A8%A1%E5%9E%8B%E7%BB%BC%E8%BF%B0.pdf
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