In this class you will learn about a variety of methods for using a computer to discover patterns in data. The methods include techniques from statistics, linear algebra, and artificial intelligence. Students will be required to solve written exercises, implement a number of machine learning algorithms and apply them to sets of data, and hand in written reports describing the results. Quizzes may also be given. Nothing will require proctoring in this course.
This course can be applied toward:
CS 440 (Introduction to Artificial Intelligence).
Dr. Charles W. Anderson is a professor of Computer Science at CSU. He graduated with a Ph.D. in computer science from the University of Massachusetts, Amherst, in 1986, and worked at GTE Laboratories in Waltham, MA, until arriving at CSU in 1991. Dr. Anderson works with neural networks, reinforcement learning, EEG pattern recognition, neural modeling, HVAC control, adaptive tutoring, computer graphics, computer vision, and software and hardware testing.