@尊重智慧財產權,請同學勿隨意影印教科書 。 Please respect the intellectual property rights, and shall not copy the textbooks arbitrarily.

科目代碼	ENC2045	課程名稱	計算語言學
英文名稱	Computational Linguistics
全/半年	半	必/選修	選修
學分數	3.0	每週授課時數	正課時數: 3.0 小時, 實驗時數: 0.0 小時
先修課程
課程簡介	Computational Linguistics (CL) is now a very active sub-discipline in applied linguistics. Its main focus is on computational text analytics, which is essentially about leveraging computational tools, techniques, and algorithms to process and understand natural language data (in spoken or textual formats). Therefore, this course aims to introduce useful strategies and common workflows that have been widely adopted by data scientists to extract useful insights from natural language data. In this course, we will focus on textual data. A selective collection of potential topics may include: • A Pipeline for Natural Language Processing • Text Normalization • Text Tokenization • Parsing and Chunking • Issues for Chinese Language Processing (Word Segmentation) • Feature Engineering and Text Vectorization • Traditional Machine Learning • Classification Models (Naive Bayes, SVM, Logistic Regression) • Common Computational Tasks (Sentiment Analysis, Text Clustering, Topic Modeling) • Deep Learning and Neural Network • Neural Language Model • Sequence Models (RNN, LSTM/GRU, Sequence-to-sequence Model, Attention-based Models) • Explainable Artificial Intelligence and Computational Linguistics This course is extremely hands-on and will guide the students through classic examples of many task-oriented implementations via in-class theme-based tutorial sessions. The main coding language used in this course is Python. We will make extensive use of the language. It is assumed that you know or will quickly learn how to code in Python. (If you are not sure if you fulfill the prerequisite, please contact the instructor first.)
課程目標		對應系所核心能力
1.　to meet the need for a genuinely theoretical introduction and basic programming techniques for linguistic purpose		碩士: 　1-1 具備深化專業知識範疇及其學術研究之能力 　2-3 具有運用多媒體及資訊科技之能力