Syllabus
Texts
This semester we will be using a linear algebra text for the majority of the semester but will supplement with material from other texts.
- Primary Text: “Linear Algebra and it’s Applications 6th ed.” by Lay, Lay, and McDonald (A PDF of the fifth edition can be found online and has most of the same content. I have also placed a physical copy of the fifth edition on reserve in the library.) Chapters 4-7 and some of 10
- Supplementary Text: “Mathematics for Machine Learning” by Deisenroth, Faisl, and Ong, Chapters 1-5 and 7
- Supplementary Text: “Calculus Volume 3” from OpenStax, Chapters 2-4
Calendar
There is a proposed calendar on the syllabus, but here I will record what we actually get through in each class.
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Assignments:
Material for assignments will be pulled from the text books, from some projects that go along with Lay’s text (projects from Lay are at bit.ly/30IM8gT)
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Previous Semester Lecture Slides
- Review of Linear Algebra: Matrix and Vector Arithmetic (Fall 2025 Edition)
- Review of Linear Algebra: Equations, Inverses, Determinants (Fall 2025 Edition)
- Review of Linear Algebra: Bases and Coordinates (Fall 2025 Edition)
- Review of Linear Algebra: Eigenvalues and Eigenvectors (Fall 2025 Edition)
- Orthogonalization, Regression, and Inner Products
- Symmetric Matrices and Basic Optimization
- Symmetric Matrices SVD and PCA
- Lines and Plains in Multiple Dimensions
- Limits and Derivatives in Multiple Dimensions