Artificial Intelligence has become ubiquitous in our society, with
applications in search,
image understanding, apps, mapping, medicine, drones, and self-driving
cars.
Recent developments in neural network (aka “deep learning”) approaches
have greatly advanced
the performance of these state-of-the-art AI resp. machine learning
systems. This lecture
is a deep dive into details of the deep learning architectures with a
focus on learning end-to-end models, particularly for image
classification.
Your will also get in touch with how to implement, train and debug
your own neural networks and gain a detailed understanding of main
approaches within the research on deep learning.
- Dozent*in: Alejandro Molina