自然語言處理概論
Introduction to Natural Language Processing
| 節 | 週三 |
|---|---|
3 10:10–11:00 | 自然語言處理概論 ED102 2 節連堂 |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
This course introduces advancements in natural language processing technology from different levels such as vocabulary, syntax, and pragmatics, demonstrating how to apply machine learning and deep learning models in natural language processing. We will also talk about how to implement commonly used models in natural language processing, enabling students to use the latest technologies to analyze documents. The course is taught in English.
Introduction to Machine Learning, Python Programming
I offer both in-person and synchronous online courses. If there is a need to switch to online-only mode, further notice will be given. The courses are mainly based on the content of the slides, and assignments are given for practical exercises.
1學期作業 3 homework、1 group presentation、1 final project 2.考試狀況 No exam 3.評量方法 Homework (individual): 60% Final Project (Group): 30% Presentation (Group): 10%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction of the Course |
| 第 2 週 | Introduction to Natural Language Processing |
| 第 3 週 | Language Modeling |
| 第 4 週 | Introduction of Machine Learning and Deep Learning |
| 第 5 週 | No Class |
| 第 6 週 | Neural Networks for NLP (Word Embedding) |
| 第 7 週 | Neural Networks for NLP (Sequence Modeling) |
| 第 8 週 | Midterm (No Class) |
| 第 9 週 | Neural Networks for NLP (Self-attention) |
| 第 10 週 | Neural Networks for NLP (Transformer) |
| 第 11 週 | Break for EMNLP |
| 第 12 週 | Generative AI for NLP |
| 第 13 週 | Generative AI for NLP |
| 第 14 週 | Break for Final Project |
| 第 15 週 | Group Presentation |
| 第 16 週 | Final Exam (No Class) |
Grus, Joel. Data science from scratch: first principles with python. O'Reilly Media, 2019. Christopher D. Manning and Hinrich Schütze, Foundations of Statistical Natural Language Processing, MIT Press. 1999.
- 時間
- by appointment
- 聯絡方式
- by e-mail