Natural Language Processing and Computational Linguistics
This course will introduce the basic technologies, methods, models, as well as cutting-edge technological progress and future development directions of text information processing and computational linguistics.
讲师
日期
2025年03月24日 至 06月18日
位置
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| 周一,周三 | 13:30 - 15:05 | A3-1-103 | Zoom 16 | 468 248 1222 | BIMSA |
修课要求
Computer Science, Machine Learning, Statistics, Python
课程大纲
1. Basic Text Processing 1）- Regular Expressions,Tokenization
2. Basic Text Processing 2）- Edit Distance
3. N-gram Language Models
4. Naive Bayes, Text Classification, and Sentiment
5. Logistic Regression for Text Classification
6. Vector Semantics and Embeddings
7. Neural Networks
8. Neural Language Models
9. Transformers
10. Large Language Models
11. NLP Applications 1) -- Chatbots and Dialogue Systems
12. NLP Applications 2) -- Sequence Labeling for Parts of Speech and Named Entities
2. Basic Text Processing 2）- Edit Distance
3. N-gram Language Models
4. Naive Bayes, Text Classification, and Sentiment
5. Logistic Regression for Text Classification
6. Vector Semantics and Embeddings
7. Neural Networks
8. Neural Language Models
9. Transformers
10. Large Language Models
11. NLP Applications 1) -- Chatbots and Dialogue Systems
12. NLP Applications 2) -- Sequence Labeling for Parts of Speech and Named Entities
参考资料
[1] Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition with Language Models (Third Edition draft)
Daniel Jurafsky, Stanford University
James H. Martin, University of Colorado at Boulder
Daniel Jurafsky, Stanford University
James H. Martin, University of Colorado at Boulder
听众
Advanced Undergraduate
, Graduate
, 博士后
视频公开
公开
笔记公开
公开
语言
中文
, 英文
讲师介绍
谢海华2015年在美国爱荷华州立大学取得计算机博士学位，之后在北京大学数字出版技术国家重点实验室担任高级研究员和知识服务方向负责人，于2021年10月全职入职BIMSA。他的研究方向包括：自然语言处理和知识服务。他发表论文数量超过20篇，拥有7项发明专利，入选北京市高水平人才项目并当选北京市杰出专家。