Instructor: Dr.
Shieu-Hong Lin Course
Website: csci.biola.edu/csci440/
Class: M
W
Course objectives:[1]
¡P
Gain a general
understanding of Artificial Intelligence research and the applications in
speech recognition, computer vision, natural language processing, data mining,
machine learning, and automatic reasoning through reading and programming
assignments.
¡P
Establish the
in-depth understanding of the mathematical and algorithmic framework underlying
the very important subject of machine learning.
¡P
Learn to use
software and programming environments such as WEKA for data mining, R for
statistical computing, OpenCV
for computer vision, or 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 software and programming environments.
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 Luis Torgo, Data Mining with R: Learning with Case Studies, Chapman and Hall/CRC, 2011.
Grading Policy
1.Attendance & participation
10%
2.Reading 15%
3.Homework& programming assignments 45%
4.Project 15%
5.Exam 15%
Weekly progress reports: They are always due on Wednesdays. Download the template file from the class website. By Wednesday each week, you should spend around 5~10 minutes to add the latest progress in reading and programming made since last Wednesday into the report, and email the file to as an attachment to Dr. Lin.
Project: You¡¦ll need to conduct an in-depth project on data
mining using WEKA or R, or on computer vision using OpenCV,
or on natural language processing using NLTK, or on knowledge representation
and automatic reasoning using Eclipse 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 More on machine learning and data
mining using R
¡P
Week 11 Computer
vision and machine learning
¡P
Week 12 Natural
language processing and machine learning
¡P
Week 13 Knowledge
representation: general game playing
¡P
Week 14 Automatic
reasoning: 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.)