# DSC210: Numerical Linear Algebra (FA23)

Numerical Linear Algebra is a fundamental tool for data science and machine learning. This course will introduce basic concepts and provide a mathematical foundation for research in machine learning and data science. We will discuss how numerical linear algebra is useful and essential in several key machine learning and data science topics.

## Course Contents

Fundamentals (matrix, orthogonality, norms, SVD, QR factorization, Gram-Schmidt Orthogonalization, Numerical methods), Application to Machine Learning and Data science topics (Least squares problems, Principal component analysis).

## Course Staff

- Instructor: Prof. Lily Weng, HDSI
- TA:
- Akshay Kulkarni, CSE
- Yilan Chen, CSE
- Ge Yan, CSE
- Tuomas Oikarinen, CSE

For contact information, see Staff page.

## Course Logistics

For course logistics, see Logistics page.

## Course Timeline

For course timeline, slides, and scribe-notes, see Course Timeline page.