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
Midterm 1 is on Friday, May 22nd from 1-3PM in 1690 BBB. See the Midterm 1 Logistics page for more details.
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 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; Midterm 1
- Mon May 18
- Tue May 19
LEC 5 Vector Spaces and Subspaces
- Wed May 20
Lab 5 Vector Spaces, Subspaces, Bases, and Dimension
HW 4 Projections, Span, and Linear Independence
You cannot use slip days on Homework 4.
- Thu May 21
LEC 6 Matrices, Exam Review
- Fri May 22
EXAM Midterm 1 (1-3PM, 1690 BBB; see logistics here)
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
- Thu May 28
LEC 8 Linear Transformations, Inverses, and Projections
HW 5 Matrices
- Sun May 31
HW 6 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
HW 7 Linear Transformations and Projections
- 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, 1690 BBB)
- Thu Jun 11
LEC 11 Eigenvalues, Eigenvectors, and Diagonalization
- Sun Jun 14
HW 9 Multiple Linear Regression, Gradients
Week 7: SVD and PCA
- Mon Jun 15
Lab 10 Convexity, Eigenvalues and Eigenvectors
- Tue Jun 16
LEC 12 Spectral Theorem, Singular Value Decomposition
- Wed Jun 17
Lab 11 Adjacency Matrices and Diagonalization
- Thu Jun 18
LEC 13 Principal Components Analysis and Applications
HW 10 Eigenvalues and Eigenvectors
- Sun Jun 21
HW 11 Singular Value Decomposition