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computational-advertising-note
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计算广告学习笔记
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Awesome-Click-Through-Rate-Prediction
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A curated list of papers on click-through-rate (CTR) prediction.
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computational-advertising-note
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# 计算广告 RTB 学习 已迁移到 https://gitee.com/wdxtub/computational-advertising-note ## 学习笔记 + 10 分 `advanced-analytics-with-spark` 《Spark 高级数据分析》 ,使用 py3+spark2 + 8 分 `pyspark-in-action` 《Python+Spark2.0+Hadoop机器学习与大数据实战》 ,使用 py36 + `ctr-in-action` CTR 预估实战,使用 pyctr ## 数据集 来自 Kaggle 比赛 + [Click-Through Rate Prediction](https://www.kaggle.com/c/avazu-ctr-prediction/data) 1GB + [KDD Cup 2012, Track 2](https://www.kaggle.com/c/kddcup2012-track2/data) 10GB + [Avito Context Ad Clicks](https://www.kaggle.com/c/avito-context-ad-clicks/data) 18GB + [Outbrain Click Prediction](https://www.kaggle.com/c/outbrain-click-prediction/data) 36GB ## 论文 + [Paper Collection of Real-Time Bidding](https://github.com/wnzhang/rtb-papers) ## 参考资料 + [CTR预估入门及各种模型介绍](https://www.mayi888.com/archives/54482) + [DSP的bidding算法](http://www.huxmarket.com/detail/2966)