Mathematics for Machine Learning 🧠
EECS 245, Spring 2026 🌸 at the University of Michigan
Suraj Rampure he/him
Lecture: TuTh 1-4PM, 1690 BBB
Office Hours: Before/after lecture and by appointment
Welcome to EECS 245! Make sure to read the Syllabus and join our Slack workspace. Note that the date of Midterm 1 has been moved; scroll down for the latest date.
The lecture recordings this semester are private to the students in the class, given the small class size. For publicly available recordings, see last semester’s course website.
Week 1: Introduction and Regression
- Tue May 5
LEC 1 Introduction, Models, and Loss Functions
📝 In-Class Notes📺 Recording📺 Recording (Part 1)📺 Recording (Part 2)The posted recordings are from last semester, though ignore the syllabus details discussed, as those are different this semester.
- Wed May 6
Lab 1 Math Foundations and Environment Setup
- Thu May 7
LEC 2 Empirical Risk Minimization and Simple Linear Regression
- Sun May 10
SUR Welcome Survey
HW 1 Means, Sums, and Calculus
Week 2: Vectors and Linear Independence
- Mon May 11
- Tue May 12
LEC 3 Vectors, Orthogonality, and the Dot Product
- Wed May 13
Lab 3 Vectors and the Dot Product
HW 2 Empirical Risk and Simple Linear Regression
- Thu May 14
LEC 4 Projections, Span, and Linear Independence
- Sun May 17
HW 3 Vectors and the Dot Product
Week 3: Vector Spaces and Matrices
- Mon May 18
Lab 4 Projections, Span, and Linear Independence
- Tue May 19
LEC 5 Vector Spaces, Subspaces, Bases, and Dimension
- Wed May 20
Lab 5 Vector Spaces, Subspaces, Bases, and Dimension
HW 4 Projections and Spans
- Thu May 21
LEC 6 Matrices, Exam Review
- Fri May 22
EXAM Midterm 1 (1-3PM)
Note that this is the updated date/time.
- Sun May 24
HW 5 Linear Independence and Subspaces
Week 4: Linear Transformations
- Tue May 26
LEC 7 Rank, Column Space, Null Space, and Inverses
- Wed May 27
Lab 6 Rank, Column Space, Null Space, and Inverses
HW 6 Matrices
- Thu May 28
LEC 8 Linear Transformations, Inverses, and Projections
- Sun May 31
HW 7 Rank and Inverses
Week 5: Regression and Optimization
- Mon Jun 1
Lab 7 Inverses and Projections
- Tue Jun 2
LEC 9 Multiple Linear Regression and the Gradient Vector
- Wed Jun 3
Lab 8 Multiple Linear Regression; The Gradient Vector
- Thu Jun 4
LEC 10 Gradient Descent and Convexity
- Sun Jun 7
HW 8 Projections; Regression using Linear Algebra
Week 6: Midterm 2 and Eigenvalues
- Mon Jun 8
Lab 9 Gradient Descent and Convexity
- Tue Jun 9
EXAM Midterm 2 (1-3PM)
- Thu Jun 11
LEC 11 Eigenvalues, Eigenvectors, and Diagonalization
- Sun Jun 14
HW 9 Multiple Linear Regression, Gradients