CSE 6363 - Machine Learning (8-week)
⭓Description
This is the course page for CSE 6363 - Machine Learning (8-week) 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
- Shovon Pereira (snp3941 (at) mavs (dot) uta (dot) edu)
Office Hours
| Days | Time | Location |
|---|---|---|
| Mo-Fri | 12PM - 1PM | 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 13 | Course Introduction, Supervised Learning | |
| January 15 | Regularization, Probability Theory, and Linear Discriminant Analysis | |
| January 22 | Naive Bayes Classifier, Support Vector Machine | |
| January 27 | Support Vector Machine, Neural Networks | |
| January 29 | Decision Trees, Boosting and Bagging | |
| February 3 | Gradient Boosting, Deep Learning | |
| February 5 | CNNs for Object Detection, Python for Deep Learning | |
| February 10 | Optimization for Deep Learning, Recurrent Neural Networks | |
| February 12 | Transformers | |
| February 17 | Unsupervised Learning | |
| February 19 | Reinforcement Learning | |
| February 24 | Natural Language Processing |
|
| February 26 | Large Language Models |
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| March 3 | Special Topics |
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| March 5 | Project Presentations |
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