算法工程

推荐系统解构:

 https://mp.weixin.qq.com/s/LO9KV7foJyVJRFPjIAT1Ew

推荐精排模型之经典排序模型:

https://mp.weixin.qq.com/s?__biz=MzI5ODk5MDU1MQ==&mid=2247483886&idx=1&sn=c320eb7d3e35bbd163ce9512e52cb850&scene=21#wechat_redirect

召回算法实践总结:

https://zhuanlan.zhihu.com/p/139256086

线上线下效果一致性杂谈 

https://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247491052&idx=1&sn=2ea8a78ee3727e36e4861dfb6f42d3f1&chksm=a6926e0191e5e717a6d4555746ac7428a1dfa7199f078e889dfc90c51fe36515f615a34c3208&scene=178&cur_album_id=1361608965674893313#rd

增量学习在CTR模型训练中的实践

https://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247490613&idx=1&sn=8ce1906cda4a639bc630b80e145fec1c&chksm=a6926fd891e5e6ce7eec9b73907a6c7854afa985df3b183b0fcab68cce571a6bd09dd1eee0ad&scene=178&cur_album_id=1361608965674893313#rd

Ctr 预估之 Calibration

https://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247484484&idx=1&sn=452f2996a0ae4c5639a41d3bef73668f&chksm=a69277a991e5febf1385730c5f539213348b804053b2fed8779fecff6b4c66dd7cb32ee57bf9&scene=178&cur_album_id=1361608965674893313#rd

EMBEDDING 在大厂推荐场景中的工程化实践

https://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247486079&idx=1&sn=7d2289dbbba53fce268587d1fb480b27&chksm=a692799291e5f084a19bce5b6a44941474f0c0b4fae011ab12e242b45479caf82fa0d11e2c29&scene=178&cur_album_id=1361608965674893313#rd

推荐系统主流召回方法综述

https://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247485429&idx=1&sn=82cd0bcc451cc25e6a10cfb4930fbe1b&chksm=a692741891e5fd0efbb810d1a3fdab9124234b4be0fc2d1394ced1fb624c596fd6482ace5456&scene=178&cur_album_id=1361608965674893313#rd

2021年浅谈多任务学习

 https://mp.weixin.qq.com/s/2I9iPFP_BkSjSEm7xJiHPQ

深度学习中的知识蒸馏技术

https://mp.weixin.qq.com/s/pth5nb1Q4SpO-iAhjmgfcA