CS 539: Machine Learning :: Summer 2025

Primary Textbook is

• (Flach) Machine Learning: The Art and Science of Algorithms That Make Sense of Data by Peter Flach, Cambridge University Press.

Additional course readings will be drawn from the following textbooks:

• (LfD) Learning From Data by Y. S. Abu-Mostafa, M. Magdon-Ismail, and H.T. Lin., AML Book
• (Mitchell) Machine Learning by Tom Mitchell, McGraw Hill
• Machine Learning Lecture Notes by Andrew Ng
• (Sutton & Barto) Reinforcement Learning: An Introduction by Sutton and Barto, MIT Press
• (DLP) Deep Learning with Python by François Chollet, Manning Publications
• Selected Research Papers

Tentative Schedule (subject to change)

Week #	Date	Topic	Readings	Homework	Quiz	Project
1	5/27	Course overview & Machine Learning, Framing a Learning Problem; Supervised Learning & Decision Trees	Flach: Prologue & Ch. 1, The Discipline of Machine Learning; Mitchell: Ch. 3
2	6/3	Decision Trees & Overfitting, Evaluation, Linear Regression; Gradient Descent	Flach: 2.1-3.2, LfD: 1.1,3.2.1, Flach: 7.1, Optional linear algebra review	HW1 out		Form a team by June 10
3	6/10	Linear Regression; Regularization, Perceptron; Logistic Regression	Flach: 7.1, 7.2 Basis functions LfD: 3.3	HW2 out	Quiz1
4	6/17	Logistic Regression; Evaluation; Optimizers; Bias & Variance; Neural Network	LfD: 2.3, Learning Theory Notes Deep Learning Backpropagation
5	6/24	Deep Learning; PyTorch Basics and Example	DLP: 5.1; Convolutional Neural Networks	HW3 out	Quiz2
6	7/1	Deep Learning; Ensemble Methods;	DLP: 6.2; Flach: 11			Proposal due by July 1
7	7/8	Unsupervised Learning:  K-Means; GMMs; Markov Decision Process;	k-means clustering Flach 8.4 Mixture of Gaussians Sutton & Barto: Ch. 3, Ch. 4, RL notes	HW4 out
8	7/15	Markov Decision Process; Reinforcement Learning;			Quiz3
9	7/22	Support Vector Machines; Text Classification; Word Vectors;	Flach: 7.3, 7.5, Bennett Distributed Representations of Words and Phrases and their Compositionality
10	7/29	Transfer Learning; Project Presentation (live session)			Quiz4 (7/29~7/30)	Website and Slides due by July 29 Peer & Self Evaluation Form by July 30