Created:
Tue 06 Sep 2011
Last modified:
Instructor
Course
- Meets:
Wed 6--9pm
- Room:
433 Ryder
Prerequisite
-
Officially, CS5100 (Foundations of Artificial Intelligence) and
CS5800 (Algorithms) are prerequisites. However, Machine Learning
is largely self-contained.
Text
- Pattern Classification (second edition)
by Duda, Hart, and Stork.
Homework
- There will be approximately six homework assignments in the first
three-quarters of the term. The exact schedule of assignments will be
posted on the syllabus page. Homework assignments will consist of a mix
of pencil-and-paper problems as well as coding/implementation.
Project
- There will be a final project which will involve coding and a written report.
Grading
- Homeworks: 3/4
- Final Project: 1/4
Academic Honesty
- All work submitted for credit must be your own.
- You may discuss the homework problems with your classmates and
Professor Aslam. You must acknowledge the people with whom you
discuss your work, and you must write up your own solutions. Any
written sources used (apart from the text) must also be
acknowledged.
- Please ask if you have any questions about academic honesty as it
applies to CS6140.
Switch to:
jaa@ccs.neu.edu