Date | Lecture | Teacher | Materials | Notes / Reading |
---|---|---|---|---|
17.02.2021 | 1. Introduction to Neural Networks | BF | slides record | McCulloch-Pitts Neuron |
24.02.2021 | 2. The Power of Neural Networks | BF | slides record | |
03.03.2021 | 3. Backpropagation | AS | slides record | |
10.03.2021 | 4. Stochastic Gradient Descent (SGD) | AS | slides record | |
17.03.2021 | 5. Convolutional Neural Networks | AS | slides record | A guide to convolution arithmetic for deep learning |
24.03.2021 | 6. Data Augmentation, Weight Initialization, Batch Normalization | BF | slides record | |
31.03.2021 | 7. Regularization Methods for NNs | AS | slides record | |
07.04.2021 | 8. Adaptive SGD Methods | AS | slides record | |
14.04.2021 | 9. Adversarial Patterns. Robust Learning Approaches | BF | slides record | |
21.04.2021 | 10. Learning Representations, Stochastic EM | AS | slides record | |
28.04.2021 | 11. Variational Autoencoders | BF | slides record | VAE tutorial |
05.05.2021 | 12. Guest lecture: Deep Metric Learning | Giorgos Tolias | slides record | |
12.05.2021 | — Rector's day — | |||
19.05.2021 | 13. Recurrent Neural Networks. Recurrent Back-Propagation | BF | slides |