CSE 6363 - Machine Learning

Spring 2025

Last updated on Jan 14, 2025

⭓Description

This is the course page for CSE 6363 - Machine Learning in Spring 2025. Here you’ll find class notes and other helpful resources. All assignments and announcements will be posted on Canvas.

Instructor Office Hours

Days	Time	Location
MoWeFri	12PM - 1PM	ERB 125
TuTh	1PM - 2PM	ERB 125

Teaching Assistant

Usha Chintha (uxc5333 (at) mavs (dot) uta (dot) edu)

Office Hours

Days	Time	Location
Mo-Fri	4PM - 5PM	Teams

⭓Course Materials

Books

Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.
Trevor Hastie, Robert Tibshirani, and Jerome Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer, 2009.
Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani, An Introduction to Statistical Learning, Springer, 2023.
Kevin Murphy, Probabilistic Machine Learning: An Introduction, MIT Press, 2022.

Resources

⭓Schedule

This schedule is tentative and may change.

Date	Topic	Materials
January 14	Course Introduction	Linear Regression
January 16	Supervised Learning	Regularization Logistic Regression
January 21	Probability Theory Review	Probability Theory Maximum Likelihood Estimation
January 23	Probabilistic Models	Linear Discriminant Analysis Naive Bayes Classifier
January 28	Using Python for Machine Learning
January 30	Kernels and Support Vector Machine	Kernel Methods Support Vector Machine