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Lectures Syllabus

Date Lecture Teacher Materials Reading
19.02.2025 1. Recap of Machine Learning, Multi-Layer Perceptron AS slides Goodefellow 5.2-5.5
26.02.2025 2. Backpropagation AS slides Implicit Layers, Chapter 1
05.03.2025 3. Convolutional Neural Networks AS slides
12.03.2025 4. Training Deep Models AS slides
19.03.2025 5. Regularization Methods for NNs AS slides Goodfellow Chapter 7
26.03.2025 6. Stochastic Gradient Descent (SGD) AS slides
02.04.2025 7. Adversarial Patterns, Robust Learning Approaches AS slides
09.04.2025 8. Adaptive Optimization Methods AS slides
16.04.2025 9. Learning Representations I: Word Vectors, Metric Learning AS slides
23.04.2025 10. Learning Representations II: Unsupervised Learning, VAE AS slides Tutorial on VAEs, t-SNE
30.04.2025 11. Graph Neural Networks GT slides
07.05.2025 12. Self-Attention, Transformers GT slides
14.05.2025 — Rector's day —
21.05.2025 13. Responsible AI GT / guest lecture Noa Garcia
courses/bev033dle/lectures.txt · Last modified: 2025/05/13 11:48 by toliageo