MAS 557 Theories and Applications of

Machine Learning

(2007 Spring Semester)

- Lecturer : 길 이 만

Office: 산업경영동 3210호; Office Hour: Tue. Thu. 15:30-16:30

- T.A. : 박 운 정

Tel: 2776; E-mail: tomato0720@kaist.ac.kr

- Scope : Machine Learning is concerned with computer programs that automatically improve their performance through experience. This course covers the theories and applications of machine learning in variety of perspectives. We cover topics such as decision trees, artificial neural networks, evaluation of learning systems, computational learning theory, support vector machines, and Bayesian belief networks.

- Prerequisites : linear algebra, probability, statistics, and scientific computation

- Text book: Lecture Note

- References :

(PC) R. Duda et al., "Pattern Classification," Wiley-Inetrscience, 2001.

(ML) T. Mitchell, "Machine Learning," McGraw-Hill, 1997.

(LD) V. Cherkassky and F. Mullier, "Learning from Data," J. Wiley, 1998.

(NN) S. Haykin, "Neural Networks," Prentice Hall, 1999.

- Web Page : http://amath.kaist.ac.kr/~nipl/mas557/

- Grading :

Homeworks --- 30%

Project ------- 30%

Exam -------- 40%(mid_term: 20%; final: 20%)