Sushil J. Louis
http://www.cse.unr.edu/
sushil
SEM 223 (784-4315)
Advanced applications. Self-organizing, self-adapting systems; cybernetics; neural networks; automated decision making and control; learning automata; expert systems application; knowledge and data engineering; pattern recognition, image processing.
Prerequisite: An undergraduate class in Artificial Intelligence
This class will use machine learning techniques to attack real world problems. We will focus on three major techniques:
For each of these techniques, you will write code to implement the technique and demonstrate learning performance on a simple (clean data) problem. A good source of clean machine learning data can be found at the University of California, Irvine's Machine Learning Repository.
Subsequently, you will apply all three techniques to a real world problem of our choosing. You may work in groups for this portion and each group member will get the same grade.
Groups are encouraged but need my permission. Project presentations will be at the end of the semester. While working on your problem, you will be asked to find, read, and present papers pertaining to your problem, or that you find interesting. Become familiar with library and internet resources. In addition to your presentations, there may be research presentations from graduate students, faculty, and other speakers.
Please look in http://www.cse.unr.edu/~sushil for pointers to
papers and other information useful for this course. I would like each
of you to set up a web page and keep a pointer to your work (graphical
and textual). All assignments will be turned in by posting them on
your web page and sending me a link. Here's a department link on
how
to set up a web page.
If you do not already have one, you will need to get an account on CSE department machines. Do this at the end of the first class. To get a CSE account, go to the IT page.
Your grade will depend on assignments, presentations, one midterm exam, and final project. I will expect to see you after each presentation to discuss the presentation and assign you a grade. Any person or group producing publishable work gets an automatic A.
Your grade will be calculated from the following table.
| Item | Percentage |
| Assignments | 30% |
| Presentations | 20% |
| Project and Report | 50% |
If I need to communicate with the class as group I'll place a notice on the class web page. You are required to check the website and your email every day. Get yourself a cs account and implement mail forwarding if you need to. Other Internet resources can be found on the class web page
Academic Success Services: Your student fees cover usage of the Math Center (784-4433 or www.unr.edu/mathcenter/), Tutoring Center (784-6801 or www.unr.edu/tutoring/), and University Writing Center (784-6030 or http://www.unr.edu/writing_center/. These centers support your classroom learning; it is your responsibility to take advantage of their services. Keep in mind that seeking help outside of class is the sign of a responsible and successful student.
This document was generated using the LaTeX2HTML translator Version 2008 (1.71)
Copyright © 1993, 1994, 1995, 1996,
Nikos Drakos,
Computer Based Learning Unit, University of Leeds.
Copyright © 1997, 1998, 1999,
Ross Moore,
Mathematics Department, Macquarie University, Sydney.
The command line arguments were:
latex2html -split 1 syl
The translation was initiated by Sushil Louis on 2012-08-27