Lectures Syllabus

Date Lecture Teacher Materials Notes / Reading
17.02.2021 1. Introduction to Neural Networks BF slides
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McCulloch-Pitts Neuron
24.02.2021 2. The Power of Neural Networks BF slides
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03.03.2021 3. Backpropagation AS slides
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10.03.2021 4. Stochastic Gradient Descent (SGD) AS slides
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17.03.2021 5. Convolutional Neural Networks AS slides
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A guide to convolution arithmetic for deep learning
24.03.2021 6. Data Augmentation, Weight Initialization, Batch Normalization BF slides
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31.03.2021 7. Regularization Methods for NNs AS slides
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07.04.2021 8. Adaptive SGD Methods AS slides
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14.04.2021 9. Adversarial Patterns. Robust Learning Approaches BF slides
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21.04.2021 10. Learning Representations, Stochastic EM AS slides
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28.04.2021 11. Variational Autoencoders BF slides
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VAE tutorial
05.05.2021 12. Guest lecture: Deep Metric Learning Giorgos Tolias slides
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12.05.2021 — Rector's day —
19.05.2021 13. Recurrent Neural Networks. Recurrent Back-Propagation BF slides
courses/bev033dle/lectures.txt · Last modified: 2021/05/24 12:53 by shekhole