图 书 馆开课单位--斯坦福大学计算与数学工程研究所
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1Deep & Cross Network for Ad Click Predictions[深度和跨网络广告点击预测]
Ruoxi Wang(斯坦福大学计算与数学工程研究所) Feature engineering has been the key to the success of many prediction models. However, the process is nontrivial and often requires manual feature en...
热度：38
Ruoxi Wang(斯坦福大学计算与数学工程研究所) Feature engineering has been the key to the success of many prediction models. However, the process is nontrivial and often requires manual feature en...
热度：38
2DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems[DCN V2：改进的深度和跨网络以及网络规模学习排名系统的实践课程]
Ruoxi Wang(斯坦福大学计算与数学工程研究所) DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems
热度：62
Ruoxi Wang(斯坦福大学计算与数学工程研究所) DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems
热度：62
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