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b222
courses
bev033dle
lectures
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Lectures Syllabus
Date
Lecture
Teacher
Materials
Notes / Reading
22.02.2023
1. Introduction to Neural Networks
BF
slides
01.03.2023
2. The Power of Neural Networks
BF
slides
08.03.2023
3. Backpropagation
AS
slides
15.03.2023
4. Stochastic Gradient Descent (SGD)
AS
slides
22.03.2023
5. Convolutional Neural Networks
AS
slides
29.03.2023
6. Weight Initialization, Batch Normalization, Resnets, Transfer Learning
BF
slides
05.04.2023
7. Regularization Methods for NNs
AS
slides
Goodfellow: 7.1-7.12
12.04.2023
8. Adaptive SGD Methods
AS
slides
19.04.2023
9. Adversarial Patterns. Robust Learning Approaches
BF
slides
26.04.2023
10. Learning Representations I: Metric Learning, Word Vectors
AS
slides
03.05.2023
11. Learning Representations II: t-SNE, Unsupervised RL
AS
slides
10.05.2023
— Rektor's day —
17.05.2023
12. Learning Representations III: Variational Autoencoders
BF
slides
24.05.2023
13. Recurrent Neural Networks, Transformer networks
BF
slides
courses/bev033dle/lectures.txt
· Last modified: 2023/05/23 22:27 by
flachbor