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Concepts in Deep Learning

8.3206

Dozenten

Lukas Niehaus

Beschreibung

We will work through the Book "Deep Learning" (https://www.deeplearningbook.org/) by Ian Goodfellow, Yoshua Bengio and Aaron Courville, which includes informations about basic topics in the field of deep learning. The course is structured as a paper presentation seminar, where the participants present topics from the book and create a demo about the topic.
In the seminar we focus on selected topics of Part II and Part III.

Part II: Modern Practical Deep Networks
- Deep Feedforward Networks
- Regularization for Deep Learning
- Optimization for Training Deep Models
- Convolutional Networks
- Sequence Modeling: Recurrent and Recursive Nets
- Practical Methodology
- Applications

Part III: Deep Learning Research
- Linear Factor Models
- Autoencoders
- Representation Learning
- Structured Probabilistic Models for Deep Learning
- Monte Carlo Methods
- Confronting the Partition Function
- Approximate Inference
- Deep Generative Models

Weitere Angaben

Ort: 93/E07
Zeiten: Fr. 10:00 - 12:00 (wöchentlich)
Erster Termin: Freitag, 01.11.2024 10:00 - 12:00, Ort: 93/E07
Veranstaltungsart: Seminar (Offizielle Lehrveranstaltungen)