Advanced Machine Learning and Neural Networks
Advanced Machine Learning and Neural Networks
Graduate Prerequisites: MET CS 521; MET CS 622, MET CS 673 or MET CS 682; MET CS 677 strongly recommended; or consent of instructor. - Theories and methods for learning from data. The course covers a variety of approaches, including Supervised and Unsupervised Learning, Regression, k-means, KNN’s, Neural Nets and Deep Learning, Recurrent Neural Nets, Rule-learning, Adversarial Learning, Bayesian Learning, and Genetic Algorithms. The underpinnings are covered: perceptrons, backpropagation, attention, and transformers. Each student focuses on two of these approaches and creates a term project.
2025SPRGMETCS767A1, Jan 21st to May 1st 2025
| Days | Start | End | Type | Bldg | Room |
|---|---|---|---|---|---|
| T | 06:00 PM | 08:45 PM | EPC | 206 |
2025SPRGMETCS767A2, Jan 21st to May 1st 2025
| Days | Start | End | Type | Bldg | Room |
|---|---|---|---|---|---|
| T | 09:00 AM | 11:45 AM | EPC | 206 |
2024FALLMETCS767A1, Sep 3rd to Dec 10th 2024
| Days | Start | End | Type | Bldg | Room |
|---|---|---|---|---|---|
| R | 06:00 PM | 08:45 PM | CAS | B06A |
2024FALLMETCS767A2, Sep 3rd to Dec 10th 2024
| Days | Start | End | Type | Bldg | Room |
|---|---|---|---|---|---|
| T | 09:00 AM | 11:45 AM | MET | 101 |
2024FALLMETCS767O2, Oct 29th to Dec 16th 2024
| Days | Start | End | Type | Bldg | Room |
|---|---|---|---|---|---|
| ARR | 12:00 AM | 12:00 AM |
2023SUM1METCS767SC1, May 24th to Aug 9th 2023
| Days | Start | End | Type | Bldg | Room |
|---|---|---|---|---|---|
| W | 06:00 PM | 09:30 PM | CAS | 324 |
2023SUM1METCS767SO1, May 9th to Jun 26th 2023
| Days | Start | End | Type | Bldg | Room |
|---|---|---|---|---|---|
| ARR | TBD | TBD | ROOM |
Format & Syllabus: