3. 강의목표
Machine learning is the study of algorithms and statistical methods that computers use to "learn" patterns and inferences in order to perform a specific task without explicit instruction. This course mainly aims at providing mathematical/statistical methods, which are essential in machine learning. A wide range of topics will be covered, including but not limited to density estimation, latent variable models, mixture models, clustering, classification, dimensionality reduction, regression, support vector machines, kernel methods, multi-layer perceptrons, and deep learning.
4. 강의선수/수강필수사항
A basic understanding of probability/statistics and linear algebra
Python programming language
5. 성적평가
Assignments: 40% (five or six assignments)
Midterm exam: 30%
Final exam: 30%
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
|
Machine Learning: A Probabilistic Perspective
|
Kevin P. Murphy
|
MIT Press
|
2012
|
0262018020
|
|
Pattern Recognition and Machine Learning
|
Christopher M. Bishop
|
Springer
|
2013
|
8132209060
|
7. 참고문헌 및 자료
Machine Learning: A Probabilistic Perspective (by K. Murphy, 2012)
Pattern Recognition and Machine Learning (by C. Bishop, 2006, Springer)
8. 강의진도계획
https://docs.google.com/spreadsheets/d/1-Kuri0GQ_y6Xwj85tgAW8nPUg8omREo24jxEok0P_Fw/edit?usp=sharing
9. 수업운영
Lecture: 14:00-15:15 Tuesday/Thursday
Assignment: every two weeks (approx.)
Exam: midterm and final
10. 학습법 소개 및 기타사항
Online lecture - Please check PLMS
We plan to have an offline lecture based on the university policy of COVID19 except for the first two weeks.
Zoom links for the first two weeks:
- week1-1: https://postech-ac-kr.zoom.us/j/98164657780?pwd=ck84b3hMMXd4YUVGZjl6ZG1HejZHdz09
- week1-2: https://postech-ac-kr.zoom.us/j/95045361333?pwd=cDVlQWJlVVBWdGpFbll6NVRnOU1ndz09
- week2-1: https://postech-ac-kr.zoom.us/j/99185373382?pwd=em1hM0NZK0xYM2JsMGhJbVBIR3NnZz09
- week2-2: https://postech-ac-kr.zoom.us/j/94618477956?pwd=am1VblBJT1A1d0RzcWh2QndhQzdodz09
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청