EEE126 Linear Algebra

Updated:


2024-2025 Spring

Weekly schedule

Week Part Topic Problem Session (PS)
1 Vectors Introduction, vectors (fundamentals), linear functions, norm and distance, clustering no PS
2 Vectors, matrices Linear independence, matrix fundamentals 08:30 - 09:30
3 Matrices Linear equations, matrix multiplication no PS
4 Matrices Matrix factorizations, matrix inverses 08:30 - 09:30
5 Matrices Solving linear equations, determinant no PS
6 Matrices Eigenvalues, eigenvectors 08:30 - 09:30
7 Matrices Diagonalization, dynamical systems 08:30 - 09:30
8   Midterm exam  
9 Matrices Symmetric matrices, positive definiteness no PS
10 Matrices Singular value decomposition 08:30 - 09:30
11 Least squares Fundamentals, data fitting, classification no PS
12 Least squares Multi-objective and constrained least squares 08:30 - 09:30
13 Least squares Nonlinear least squares no PS
14 Engineering applications Introduction to optimization and machine learning 08:30 - 09:30
15 Engineering applications Estimation and control, autonomous driving no PS

Resources

textbook: Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares (Boyd&Vandenberghe) (main textbook for the course)

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