ECE-6524: Deep Learning
Description: Advanced concepts in Machine Learning and Deep Learning. Models (multi-layer perceptrons, convolutional neural networks, memory networks), learning algorithms (backpropagation, stochastic sub-gradient descent, dropout), connections to structured predictions (Boltzmann machines, unrolled belief propagation), and applications to perception and Artificial Intelligence (AI) problems (image classification, detection, and segmentation; image captioning; visual question answering; automatic game playing).
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 10
Average GPA: 3.78 (A)
Strict A Rate (No A-) : 71.41%
Average Withdrawal Rate: 0.00%
| Jianhua Xuan | 2024 | 84.9% | 12.9% | 0.9% | 0.0% | 1.3% | 0.0% | 3.77 | 8 |
| Jia Bin Huang | 2020 | 90.7% | 6.8% | 1.3% | 0.0% | 1.3% | 0.0% | 3.82 | 2 |