ECE-5424: Advanced Machine Learning
Description: Algorithms and principles involved in machine learning; focus on perception problems arising in computer vision, natural language processing and robotics; fundamentals of representing uncertainty, learning from data, supervised learning, ensemble methods, unsupervised learning, structured models, learning theory and reinforcement learning; design and analysis of machine perception systems; design and implementation of a technical project applied to real-world datasets (images, text, robotics). Pre: Graduate standing.
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 19
Average GPA: 3.84 (rounds to A-)
Strict A Rate (No A-) : 71.98%
Average Withdrawal Rate: 0.10%
| Bert Huang | 2021 | 84.0% | 14.4% | 1.1% | 0.6% | 0.0% | 0.0% | 3.82 | 4 |
| Yue J Wang | 2024 | 96.4% | 3.3% | 0.0% | 0.0% | 0.0% | 0.2% | 3.91 | 8 |
| Creed F Jones | 2022 | 86.1% | 14.0% | 0.0% | 0.0% | 0.0% | 0.0% | 3.80 | 1 |
| Ming Jin | 2023 | 84.2% | 10.3% | 2.4% | 1.9% | 1.1% | 0.0% | 3.70 | 2 |
| Ismini Lourentzou | 2023 | 95.5% | 4.5% | 0.0% | 0.0% | 0.0% | 0.0% | 3.91 | 2 |
| Hoda M Eldardiry | 2020 | 92.3% | 7.7% | 0.0% | 0.0% | 0.0% | 0.0% | 3.85 | 1 |
| Wei Zhou | 2022 | 72.7% | 27.3% | 0.0% | 0.0% | 0.0% | 0.0% | 3.67 | 1 |