Topics on Artificial Intelligence

CSCI 440, fall semester, 2014

 

Instructor: Dr. Shieu-Hong Lin      

Class:        T Th 3:00~4:15am Business 209

Office Hours: Wednesday 12:00-1:00pm, Thursday 10:30~11:30am

 

Course objectives:[1] 

P       Gain a broad understanding of Artificial Intelligence research and the applications in speech recognition, machine learning and data mining, natural language processing, search, and automatic reasoning.

P       Establish the in-depth understanding of the mathematical and algorithmic framework underlying the very important subject of machine learning, including a series of hands-on assignments on hidden Markov models.

P       Learn to use tools and programming environments such as WEKA for data mining and NLTK for natural language processing.  

P       Cultivate the problem solving capability based on the in-depth understanding of machine learning or other selected subject through hands-on study projects using the related tools and programming environments.

 

Related textbooks:

P       Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd ed. Prentice Hall, 2009.

P       I.Witten & E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, 3rd ed., Morgan Kaufmann, 2011.

P       Steven Bird, Ewan Klein, and Edward Loper, Natural Language Processing with Python, O'Reilly, 2009.

 

 

 

 

 

Grading Policy

1. Reading & participation                                                                  15%

2. Homework & programming assignments                                       45%

3. Study project                                                                                   15%

4. Exam                                                                                               25%

 

Weekly progress reports: They are always due on Tuesdays with grace period to Thursday.

 

Study project: Youll need to conduct a study project on selected subjects such as data mining using WEKA or R, or on natural language processing using NLTK, or on knowledge representation and automatic reasoning using the Eclipse Constraint Logic Programming Language for general game playing.  

 

Tentative Schedule

P       Week 1                  Perspectives of artificial intelligence

P       Weeks 2-4             Speech recognition and spelling recognition

P       Weeks 5-7             Introduction to WEKA and machine learning

P       Weeks 8-10           Natural language processing using NLTK

P       Weeks 11~13        Search: Planning andTemporal Reasoning

P       Weeks 14~15                Knowledge representation: general game playing

P       Week 15                Project presentation



[1] Students desiring accommodations on the basis of physical, learning, or psychological disability for this class are to contact Disability Services.  Disability Services is located in the Learning Center (upstairs in the Biola Library) and cab e reached by calling 562-906+4542 or extension 4542 from campus.)