- English
- فارسی
NMfDS-402-1
- Python programming
- Matrix decompositins such as LU, QR, NMF, SVD with applications in Data Science
- PCA and least squares problem with applications in Data Science
- Numerical methods for the eigenvalue problem and iterative methods such Arnoldi and Lanczos methods
Prerequisites:
- Numerical analysis
- Linear algebra
- A scientific programming language such as MATLAB and Python
Grading Policy:
- 4 points for homeworks
- 4 points for projects
- 4 points for seminars
- 4 points miterm examination
- 4 points final examination
Teacher Assistants:
Dr. M. Ramezani
Time:
Sundays & Tuesdays 10-12
Term:
Fall 2023
Grade:
Graduate