2021-Spring App. of Mathematics and Big Data (MATH532) The course syllabus

1.Course Information

Course No. MATH532 Section 01 Credit 3.00
Category Major elective Course Type prerequisites
Postechian Core Competence
Hours Grading Scale G

2. Instructor Information

Hwang Hyung Ju Name Hwang Hyung Ju Department Dept. of Mathematics
Email address hjhwang@postech.ac.kr Homepage http://hjhwang.postech.ac.kr
Office 279-3056 Office Phone 279-2056
Office Hours

3. Course Objectives

본 강좌에서는 현재 주목받고 있는 데이터 분석 및 Machine learning의 기초 개념을 수학적인 방법론을 이용하여 이해한다. 이를 바탕으로 한 Machine learning 알고리즘을 직접 구현해보고, 더 나아가 최신 동향을 분석해본다.

4. Prerequisites & require

확률 및 통계

5. Grading

- 출석 10%
- 발표: 10%
- 숙제: 40%
- 중간고사 20%
- 기말고사 20%

6. Course Materials

Title Author Publisher Publication
Year/Edition		 ISBN
The Elements of Statistical Learning, Data Mining, Inference, Second Edition Hastie, Trevor, Tibshirani, Robert, Friedman, Jerome 0000

7. Course References

8. Course Plan

Week 1 Basic Probability Theory I
Week 2 Basic Probability Theory II
Week 3 Linear Methods for Regression and Classification
Week 4 EM Algorithm
Week 5 Kernel Methods and Support Vector Machine
Week 6 Model Selection
Week 7 Ensemble Methods and Random Forest
Week 8 Midterm
Week 9 Dimensional Reduction
Week 10 Gradient Descent
Week 11 Neural Networks I
Week 12 Neural Networks II
Week 13 Clustering Methods
Week 14 Graphical Models
Week 15 Presentation
Week 16 Final

9. Course Operation

자세한 내용은 추후 공지

10. How to Teach & Remark

11. Supports for Students with a Disability

- Taking Course: interpreting services (for hearing impairment), Mobility and preferential seating assistances (for developmental disability), Note taking(for all kinds of disabilities) and etc.

- Taking Exam: Extended exam period (for all kinds of disabilities, if needed), Magnified exam papers (for sight disability), and etc.

- Please contact Center for Students with Disabilities (279-2434) for additional assistance

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