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

There is a proposed calendar on the syllabus, but here I will record what we actually get through in each class.

…
9/16/2026: We went over the slides on GitHub and Code Spaces, looked through the Jupyter Notebook introduction linear algebra operations in Python, and then went through the third Review of Linear Algebra slide deck. We will finish the review next week and have the Unit 1 exam the week after. Please be sure to review the slide decks and your notes.
9/9/2026: We started class by reviewing the material we covered the previous week. We will do the same thing next week, please review your notes so that it goes more smoothly. We thne worked through the second set of review slides. Next week, after review, we will look at how we will be using GitHub in this class, please create a personal fork of the repository for the class Link to Class Repository: https://github.com/cfroccajr/Mathematics-for-Machine-Learning.git. Here is a slide deck introducing some basics of what we will be looking at next week: GitHub and Code Spaces Slide Deck Link
9/2/2026: We covered the syllabus and the material in the first set of slides. We will look at the second set of slides and Github/Jupyter notebooks next time.

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)