CS-4824: 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: 3.07 (rounds to B)
Strict A Rate (No A-) : 26.99%
Average Withdrawal Rate: 9.12%
| Chris L Wyatt | 2022 | 16.1% | 32.9% | 17.2% | 13.0% | 3.5% | 17.3% | 2.50 | 4 |
| Ming Jin | 2024 | 38.2% | 35.7% | 12.2% | 0.5% | 2.5% | 10.9% | 3.17 | 5 |
| Debarati Bhattacharya | 2024 | 43.6% | 26.4% | 9.2% | 7.5% | 7.5% | 6.0% | 2.96 | 2 |
| Dawei Zhou | 2023 | 65.6% | 25.0% | 3.1% | 0.0% | 0.0% | 6.3% | 3.66 | 1 |
| Hoda M Eldardiry | 2024 | 52.4% | 35.0% | 2.5% | 2.5% | 0.0% | 7.5% | 3.43 | 1 |
| Amr E Hilal | 2023 | 34.2% | 33.0% | 17.1% | 8.7% | 2.5% | 4.6% | 2.93 | 4 |
| Bert Huang | 2023 | 56.0% | 20.8% | 7.1% | 5.6% | 2.1% | 8.2% | 3.31 | 3 |
| Debswapna Bhattacharya | 2024 | 63.3% | 14.3% | 10.2% | 4.0% | 2.1% | 6.1% | 3.41 | 1 |
| Hongjie Chen | 2022 | 66.7% | 11.1% | 11.1% | 0.0% | 0.0% | 11.1% | 3.55 | 1 |
| Anuj Karpatne | 2020 | 53.0% | 23.5% | 17.7% | 0.0% | 5.9% | 0.0% | 3.25 | 1 |