Welcome to EECS 245! Make sure to read the syllabus and complete the action items in the Getting Started section.

Mathematics for Machine Learning 🧠

EECS 245, Fall 2026 at the University of Michigan

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Week 1: Welcome! 👋

Tue Sep 1

LEC 1 Introduction

Wed Sep 2

LAB 1 Math Foundations and Environment Setup

Thu Sep 3

LEC 2 Models and Loss Functions

Week 2: Linear Regression

Tue Sep 8

LEC 3 Empirical Risk and Simple Linear Regression

Wed Sep 9

LAB 2 Empirical Risk and Simple Linear Regression

Thu Sep 10

LEC 4 Simple Linear Regression

Fri Sep 11

HW 1 Means, Sums, and Calculus

SUR Welcome Survey

Week 3: Vectors

Tue Sep 15

LEC 5 Vectors

Wed Sep 16

LAB 3 Simple Linear Regression and Partial Derivatives

Thu Sep 17

LEC 6 Orthogonality and the Dot Product

Fri Sep 18

HW 2 Empirical Risk and Simple Linear Regression

Week 4: Projections and Linear Independence

Tue Sep 22

LEC 7 Projections

Wed Sep 23

LAB 4 Orthogonality and Projections

Thu Sep 24

LEC 8 Span and Linear Independence

Fri Sep 25

HW 3 Vectors and the Dot Product

Week 5: Vector Spaces and Subspaces

Tue Sep 29

LEC 9 Vector Spaces and Subspaces

Wed Sep 30

LAB 5 Projections, Span, and Linear Independence

Thu Oct 1

LEC 10 Bases and Dimension

Fri Oct 2

HW 4 Projections, Span, and Linear Independence

Week 6: Midterm 1; Matrices

Tue Oct 6

REV Midterm 1 Review and Office Hours

EXAM Midterm 1 (7-9PM; location TBD)

Thu Oct 8

LEC 11 Matrices

Week 7: Rank and Inverses

Tue Oct 13

LEC 12 Rank and Column Space

Wed Oct 14

LAB 6 Rank, Column Space, and Null Space

Thu Oct 15

LEC 13 Null Space, Rank-Nullity, and Inverses

Fri Oct 16

HW 5 Matrices

Week 8: Fall Break 🍂; Linear Transformations

Tue Oct 20

No Lecture: Fall Break 🍂

Wed Oct 21

LAB 7 Rank, Column Space, Null Space, and Inverses

Thu Oct 22

LEC 14 Inverses and Linear Transformations

Fri Oct 23

HW 6 Rank and Inverses

Week 9: Projections and Regression

Tue Oct 27

LEC 15 Projections, Revisited

Wed Oct 28

LAB 8 Inverses and Projections

Thu Oct 29

LEC 16 Multiple Linear Regression

Fri Oct 30

HW 7 Inverses, Projecting onto the Column Space

Week 10: Gradients

Tue Nov 3

LEC 17 The Gradient Vector

Wed Nov 4

LAB 9 Multiple Linear Regression and Gradients

Thu Nov 5

LEC 18 Gradients and Gradient Descent

Fri Nov 6

HW 8 Regression using Linear Algebra

Week 11: Gradient Descent and Eigenvalues

Tue Nov 10

LEC 19 Gradient Descent and Convexity

Wed Nov 11

LAB 10 Gradient Descent and Convexity

Thu Nov 12

LEC 20 Eigenvalues and Eigenvectors

Fri Nov 13

HW 9 Multiple Linear Regression and Gradients

Week 12: Midterm 2; Eigenvalues

Tue Nov 17

REV Midterm 2 Review and Office Hours

EXAM Midterm 2 (7-9PM; location TBD)

Thu Nov 19

LEC 21 Eigenvalues and Eigenvectors, Continued

Week 13: Eigenvalues; Thanksgiving 🍁

Mon Nov 23

HW 10 Practical Machine Learning, Eigenvalues

Tue Nov 24

LEC 22 Adjacency Matrices and Diagonalization

Wed Nov 25

No Lab: Thanksgiving 🍁

Thu Nov 26

No Lecture: Thanksgiving 🍁

Week 14: Diagonalization and SVD

Tue Dec 1

LEC 23 Diagonalization, Spectral Theorem, SVD

Wed Dec 2

LAB 11 Diagonalization, Spectral Theorem, SVD

Thu Dec 3

LEC 24 Singular Value Decomposition

Fri Dec 4

HW 11 Diagonalization

Week 15: SVD and PCA

Tue Dec 8

LEC 25 Principal Components Analysis

Wed Dec 9

LAB 12 SVD and PCA

Thu Dec 10

LEC 26 Principal Components Analysis, Continued

Fri Dec 11

HW 12 SVD and PCA

Week 16: Final Exam

Wed Dec 16

EXAM Final Exam (1:30–3:30PM)