ECE-4424: 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). A grade of C- or better in prerequisites.
Pathways: N/A
Course Hours: 3 credits
Sections Taught: 23
Average GPA: 2.97 (B)
Strict A Rate (No A-) : 22.73%
Average Withdrawal Rate: 8.62%
| Amr E Hilal | 2023 | 12.1% | 47.3% | 15.6% | 16.0% | 5.0% | 4.0% | 2.43 | 4 |
| Hongjie Chen | 2022 | 100.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 3.91 | 1 |
| Stefan M Lee | 2016 | 42.9% | 7.1% | 14.2% | 7.1% | 14.3% | 14.3% | 2.64 | 1 |
| Dawei Zhou | 2023 | 42.9% | 35.7% | 7.1% | 0.0% | 0.0% | 14.3% | 3.34 | 1 |
| Hoda M Eldardiry | 2024 | 35.7% | 35.7% | 14.2% | 0.0% | 0.0% | 14.3% | 3.25 | 1 |
| Bert Huang | 2023 | 59.8% | 27.9% | 7.4% | 1.8% | 0.0% | 3.1% | 3.48 | 4 |
| Chris L Wyatt | 2022 | 6.4% | 28.6% | 22.4% | 9.4% | 5.6% | 27.6% | 2.23 | 4 |
| Anuj Karpatne | 2020 | 31.6% | 42.1% | 21.1% | 0.0% | 5.3% | 0.0% | 3.01 | 1 |
| Ming Jin | 2023 | 46.9% | 40.5% | 9.8% | 1.1% | 0.8% | 0.9% | 3.30 | 4 |
| Debarati Bhattacharya | 2024 | 46.6% | 29.1% | 11.3% | 5.2% | 1.3% | 6.5% | 3.22 | 2 |