Department of Computer Engineering, Seoul National University
Instructor: Prof. Byoung-Tak Zhang
TAs: Suk-Joon Kim and Soo-Yong Shin
Classroom: 301-101
Time: Wed 2-4pm and Fri 10-11am
Textbook: Machine Learning, T. Mitchell, McGraw-Hill, 1997.
Supplement 1: Machine Learning: A Multistrategy Approach, Vol. IV, (Eds.) R. Michalski and G. Tecuci, Morgan Kaufmann, 1994.
Supplement 2: Machine Learning: Paradigms and Methods, (Ed.) J. G. Carbonell, MIT Press, 1990.
Schedule
Week 1: Introduction (Chap 1)
Week 2: Concept Learning (Chap 2)
Week 3: Decision Tree Learning (Chap 3)
Week 4: Artificial Neural Networks (Chap 4)
Week 5: Bayesian Learning (Chap 6)
Week 6: Midterm Exam
Week 7: Computational Learning Theory (Chap 7)
Week 8: Instance-Based Learning (Chap 8)
Week 9: Genetic Algorithms (Chap 9)
Week 10: Learning Sets of Rules (Chap 10)
Week 11: Analytical Learning (Chap 11), Combining Inductive and Analytical Learning (Chap 12) May 13: Due for the draft version of term papers
Week 12: Reinforcement Learning (Chap 13)
Week 13: (May 27) Final Exam
Week 14: (June 3) Presentations A1-A10
Week 15: (June 10) Presentations A11-A20
Week 16: (Saturday, June 13, 9:00am) B1-B8 & C1-C7 (whole-day workshop, 9am-5pm) June 17: Due for the term papers and slides (by person in diskette and hard copies to TAs at 301-417)