In-Class Demos
Notebooks and code demos. You may copy and modify for use in EE 541.
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Week 1: Introduction to Deep Learning
- Fashion-MNIST Dataset — Dataset statistics, class distribution, visualization
- Minimal PyTorch Example — Two-layer network on Fashion-MNIST, training loop
- Feature Visualization — PCA projections before and after training
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Week 3: MMSE Estimation
- MMSE Estimation — Sensor estimation under Gaussian and non-Gaussian noise
- Vector LMMSE — Orthogonality verification, sample convergence, ridge regularization
- LMS Adaptive Filtering — Audio noise cancellation, step-size effects