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Merge pull request #796 from wangzhen38/aistuio
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增加aistudio直播课二维码
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frankwhzhang authored Jun 15, 2022
2 parents b3417af + 9ebe5e9 commit 3d1ee92
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4 changes: 3 additions & 1 deletion README_CN.md
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<h2 align="center">最新动态<img src="./doc/imgs/rec_new_icon.png" width="40"/></h2>

* [2022/5/18] 新增3个前沿算法:[aitm](models/multitask/aitm),[sign](models/rank/sign),[dsin](models/rank/dsin)
* [2022/6/15] 重磅福利:短视频推荐场景下的多任务学习应用实战视频直播课,欢迎扫码关注:<p align="center"><img width="200" height="200" margin="500" src="./doc/imgs/aistudio_micro_video.png"/></p>
* [2022/6/15] 新增3个前沿算法:[ESCM2](models/multitask/escm2),[MetaHeac](models/multitask/metaheac),[KIM](models/match/kim)
* [2022/5/18] 新增3个前沿算法:[AITM](models/multitask/aitm),[SIGN](models/rank/sign),[DSIN](models/rank/dsin)
* [2022/3/21] 新增[paper](./paper)目录,发布我们对21年的推荐顶会论文的分析,以及工业界的推荐论文列表,供大家参考。
* [2022/3/10] 新增5个前沿算法: [DCN_V2](models/rank/dcn_v2), [MHCN](models/recall/mhcn), [FLEN](models/rank/flen), [Dselect_K](models/multitask/dselect_k), [AutoFIS](models/rank/autofis)
* [2022/1/12] 新增AI Studio一键[在线运行](https://aistudio.baidu.com/aistudio/projectdetail/3240640)功能,可以方便快捷的在AI Studio平台上在线体验我们的模型。
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4 changes: 3 additions & 1 deletion README_EN.md
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<h2 align="center">News<img src="./doc/imgs/rec_new_icon.png" width="40"/></h2>

* [2022/5/18] Add 3 algorithms::[aitm](models/multitask/aitm),[sign](models/rank/sign),[dsin](models/rank/dsin)
* [2022/6/15] Excellent course about multi-task learning application under short video recommendation scenarios,welcome to scan the code and follow:<p align="center"><img width="200" height="200" margin="500" src="./doc/imgs/aistudio_micro_video.png"/></p>
* [2022/6/15] Add 3 algorithms:[ESCM2](models/multitask/escm2),[MetaHeac](models/multitask/metaheac),[KIM](models/match/kim)
* [2022/5/18] Add 3 algorithms::[AITM](models/multitask/aitm),[SIGN](models/rank/sign),[DSIN](models/rank/dsin)
* [2022/3/21] Add a new [paper](./paper) directory , show our analysis of the top meeting papers of the recommendation system in 2021 years and the list of recommendation system papers in the industry for your reference.
* [2022/3/10] Add 5 algorithms: [DCN_V2](models/rank/dcn_v2), [MHCN](models/recall/mhcn), [FLEN](models/rank/flen), [Dselect_K](models/multitask/dselect_k)[AutoFIS](models/rank/autofis)
* [2022/1/12] Add AI Studio [Online running](https://aistudio.baidu.com/aistudio/projectdetail/3240640) function, you can easily and quickly online experience our model on AI studio platform.
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1 change: 1 addition & 0 deletions application/multitask_on_video/readme.md
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本项目主要介绍如何使用飞桨大规模推荐算法库[PaddleRec](https://github.com/PaddlePaddle/PaddleRec) ,仅以短视频推荐场景为例,说明多任务技术的应用方法和收益,但多任务技术不仅仅可以使用于视频推荐中,也可以在比如电商场景的点击&转化(购买),信息流推荐场景的点击&点赞(评论,关注等一系列后续行为),搜索广告场景下的点击&再点击(相关广告,相关搜索,猜你喜欢等等)等场景下使用。

另有高级研发工程师直播视频讲解,欢迎扫码关注:<p align="center"><img width="200" height="200" margin="500" src="../../doc/imgs/aistudio_micro_video.png"/></p>
## 2. 什么是多任务学习
### 2.2 多任务学习的概念
多任务学习(multitask)的定义和形式有很多种。我觉得比较直观的理解是和单任务学习相对的一种机器学习方法。
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