2021-1 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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