Course Title：自然語言處理實作 
<br>
<br>(Natural Language Processing Lab)
<br>Course number：CS 563200  3 credits
<br>Instructor： Jason S. Chang 張俊盛
<br>
<br>The course consists of a set of small exercises on natural language processing based on statistical 
<br>approach. The purpose is to give students opportunity to work with real problems and data in natural 
<br>language processing. Each session will start with explanation of background, experiental data, and 
<br>snippets of code. The students are required to do the assignment in class. The instuctor and teaching 
<br>assistants will be on hand to help students.  每週準備一個題目與實驗資料，題目為基本的研究任務（通常由某
<br>一篇論文取材）。老師會先講解背景與題目（30─60分鐘），之後同學開始寫程式解決問題。過程中，如果有問題
<br>可以互相討論，或詢問助教、老師。我們要求當天做完題目，將結果展示給助教，助教根據結果的正確性與完成時間
<br>打分數，並隨時公布最新的累積分數資料。學期的分數就是每週分數的總和。
<br>
<br>Note: (1) 第一週再原訂時間（9/27 星期五上課），之後預計改為星期三下午第7,8,9堂上課。
<br>         (2) 上課地點為舊資電館 326 室（使用 iMac 電腦）。
<br>
<br>The list of topics planned for the Fall, 2013 is as follows:
<br>
<br>Topics
<br>
<br>2013
<br>9/27		1. Python introduction (file handling, n grams)
<br>
<br>10/2		2. Corpus Processing and Ngrams and Ngram Precision (BLEU)
<br>10/9 	3. Hidden Markov Model and Dynamic Programming
<br>10/16	4. POS Tagging and Brill's tagger
<br>10/23	5. NLTK and WordNet
<br>10/30	6. Extracting Collocations
<br>
<br>11/06	7. Classifying AN-VN Collocations
<br>11/13	8. Clustering Collocations
<br>11/20	全校運動會停課一次
<br>11/27	9. Class-based Baysian Model
<br>
<br>12/04	10. Finding Best Example Sentences
<br>12/11	11. EM Algorithm
<br>12/17	12. Word Alignment with IBM Model 1
<br>12/25	13. Conditional Random Field
<br>
<br>2014
<br>01/01	New Year Holiday
<br>01/08	14. Chinese Word Segmentation