CSE 6363 - Machine Learning
⭓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 |
|---|---|---|
| MoWe | 1PM - 2PM | ERB 556A |
| TuTh | 3PM - 4PM | ERB 556A |
| Fri | 9AM - 10AM | Teams |
Teaching Assistant
- Mengliang Zhang (mxz3935 (at) mavs (dot) uta (dot) edu)
Office Hours
Please contact Mengliang via email or Teams to schedule an appointment.
| Days | Time | Location |
|---|---|---|
| Thu | 2PM - 6PM | SEIR 428 |
⭓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.
Papers
Resources
⭓Schedule
This schedule is tentative and may change.
| Date | Topic | Materials |
|---|---|---|
| June 2 | Course Introduction, Supervised Learning | |
| June 4 | Supervised Learning, Logistic Regression, HW1 Out | |
| June 9 | Review of Probability Theory, Linear Discriminant Analysis | |
| June 11 | Naive Bayes, Kernels | |
| June 16 | Kernels | |
| June 18 | Support Vector Machine, Neural Networks | |
| June 23 | Backpropagation, Bias-Variance Tradeoff | |
| June 25 | Decision Trees | |
| June 30 | Boosting | |
| July 2 | Deep Learning | |
| July 7 | CANCELLED |
|
| July 9 | Convolutional Neural Networks, PyTorch Tutorial | |
| July 14 | PyTorch Lightning, Optimization for Deep learning | |
| July 16 | Attention Mechanism, Transformers | |
| July 21 | Markov Decision Processes | |
| July 23 | Reinforcement Learning |