——/疫情期间网民情绪识别大赛(完结)/
├──01-【课件】baseline代码+相关论文【图文】
| ├──baseline
| | ├──BERTbaseline.ipynb 28.42kb
| | ├──BERTbaseline_v3.ipynb 15.14kb
| | └──数据勘察.ipynb 144.61kb
| ├──相关论文
| | └──BERT.pdf 757.16kb
| └──【课件】baseline代码+相关论文.txt 0.14kb
├──02-【3.15第一次直播】疫情期间网民情绪识别赛题详解
| └──【3.15第一次直播】疫情期间网民情绪识别赛题详解.doc 16.00kb
├──03-Week1 作业1【图文】
| └──Week1 作业1.doc 16.00kb
├──04-【3月18日】第一次直播答疑
├──05-【3月21日】迁移学习-模型融合比赛专题讲解
├──06-Week 2 作业1
| └──06-Week 2 作业1.doc 20.00kb
├──07-【3月25日】第二次直播答疑
├──08-【3月28日】模型调参和文本增强比赛专题讲解
| ├──相关论文
| | ├──BERT.pdf 757.16kb
| | ├──Better Fine-Tuning via Instance Weighting for Text Classification – 副本.pdf 1.56M
| | ├──Better Fine-Tuning via Instance Weighting for Text Classification.pdf 1.56M
| | ├──Conditional BERT Contextual Augmentation – 副本.pdf 421.26kb
| | ├──Conditional BERT Contextual Augmentation.pdf 421.26kb
| | ├──Contextual Augmentation Data Augmentation by Words with Paradigmatic Relations – 副本.pdf 705.39kb
| | ├──Contextual Augmentation Data Augmentation by Words with Paradigmatic Relations.pdf 705.39kb
| | ├──Distilling the Knowledge in a Neural Network – 副本.pdf 104.13kb
| | ├──Distilling the Knowledge in a Neural Network.pdf 104.13kb
| | ├──Do Not Have Enough Data Deep Learning to the Rescue – 副本.pdf 363.84kb
| | ├──Do Not Have Enough Data Deep Learning to the Rescue.pdf 363.84kb
| | ├──EDA Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks – 副本.pdf 356.49kb
| | ├──EDA Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks.pdf 356.49kb
| | ├──Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution.pdf 417.66kb
| | ├──How to Fine-Tune BERT for Text Classification – 副本.pdf 586.95kb
| | ├──How to Fine-Tune BERT for Text Classification.pdf 586.95kb
| | ├──Improving Neural Machine Translation Models with Monolingual Data.pdf 128.51kb
| | ├──Learning Data Manipulation for Augmentation and Weighting.pdf 607.15kb
| | ├──Learning to Paraphrase for Question Answering.pdf 1.20M
| | ├──Qanet Combining local convolution with global self-attention for reading comprehension.pdf 533.32kb
| | ├──Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding.pdf 463.16kb
| | ├──SMOTE synthetic minority over-sampling technique.pdf 489.94kb
| | ├──Understanding Back-Translation at Scale.pdf 190.85kb
| | └──UNSUPERVISED DATA AUGMENTATION FOR CONSISTENCY TRAINING.pdf 1.45M
| └──【Data Fountain(NLP)】模型调参和文本增强比赛专题讲解.doc 17.50kb
├──09-Week3 作业1
| └──Week3 作业1.doc 20.50kb
├──10-第三次直播答疑
├──11-【4月4日】比赛思路进阶专题讲解
├──12-作业
| └──作业.doc 20.50kb
├──13-【Data Fountain(NLP)】比赛思路全复盘（纯干货）
├──02-【3.15第一次直播】疫情期间网民情绪识别赛题详解.mp4 308.51M
├──04-【3月18日】第一次直播答疑.mp4 438.86M
├──05-【3月21日】迁移学习-模型融合比赛专题讲解.mp4 285.27M
├──07-【3月25日】第二次直播答疑.mp4 306.36M
├──08-【3月28日】模型调参和文本增强比赛专题讲解.mp4 275.35M
├──10-第三次直播答疑.mp4 344.33M
├──11-【4月4日】比赛思路进阶专题讲解.mp4 294.75M
└──13-【Data Fountain(NLP)】比赛思路全复盘（纯干货）.mp4 259.07M