| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
Linear Algebra really will open up possibilities of working and manipulating data. There are many awesome applications of Linear Algebra in Data Science, and have broadly categorized the applications into four fields:
1. Machine learning
2. Dimensionality Reduction
3. Natural Language Processing (NLP)
4. Computer Vision
So you can deep dive further into the one(s) which grabs your future research. |
| 1.Mathematical Thinking and Logic |
| 2.Professional Knowledge in Mathematical Analysis |
| 3.Professional Knowledge in Scientific Computation |
| 5.Mathematical Modeling and Software Application |
| 6.Research in Computation and Simulation |
|
|
| topic Discussion/Production |
| Exercises |
| Discussion |
| Lecturing |
|
| Written Presentation |
| Attendance |
| Assignment |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Fundamental background review in linear algebra
|
| Week 2 |
Fundamental background review in linear algebra
|
| Week 3 |
Orthogonality and the optimization |
| Week 4 |
Orthogonality and the optimization |
| Week 5 |
SVD and image processing |
| Week 6 |
SVD and image processing |
| Week 7 |
Tensor Decomposition |
| Week 8 |
Tensor Decomposition |
| Week 9 |
Review project #1 and presentation |
| Week 10 |
Clustering and NMF |
| Week 11 |
Clustering and NMF |
| Week 12 |
Classification of Handwritten Digits |
| Week 13 |
Classification of Handwritten Digits |
| Week 14 |
PCA & MDS |
| Week 15 |
PCA & MDS |
| Week 16 |
Review project #2 and presentation |
| Week 17 |
|
| Week 18 |
|
|
| Evaluation |
Presentation(20%)
HWs and present(80%) |
| Textbook & other References |
1. Lars Elden, Matrix Methods in Data Mining and Pattern Recognition, SIAM 2007.
2. Golub & Von Loan, Matrix Computations, 3rd Ed. , John Hopkins University, 1996.
3. Yuan Yao, A Mathematical Introduction to Data Science, Bejing University, 2014 |
| Teaching Aids & Teacher's Website |
|
| Office Hours |
| Monday 2:00-4:00 PM with appointment |
| Sustainable Development Goals, SDGs |
| include experience courses：N |
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