•Introduction: different types of machine learning algorithms, theoretical background, practical aspects, structure and elements of (convolutional) neural networks
10:30
→
10:45
Coffee Break
15m
VC
VC
AIP
An der Sternwarte 16
14482 Potsdam
10:45
→
12:15
Introduction to Machine Learning: Unsupervised Learningtbd (VC)
tbd
VC
to be published
•Introduction: different types of machine learning algorithms, theoretical background, practical aspects, structure and elements of (convolutional) neural networks
12:15
→
13:15
Lunch Break
1h
VC
VC
AIP
An der Sternwarte 16
14482 Potsdam
13:15
→
15:00
Introduction to Machine Learning: Supervised learning Itbd (VC)
tbd
VC
tbd
•Introduction: different types of machine learning algorithms, theoretical background, practical aspects, structure and elements of (convolutional) neural networks
very deep neural networks: Supervised learning IItbd (VC)
tbd
VC
use of generative adversarial networks (GANs) for generation of images of galaxies with constraints - semi-supervised case (example: We want computer to generate an image of a certain type of galaxy. The image is close to indistinguishable from an observed image)
very deep neural networks: generative adversarial networkstbc (VC)
tbc
VC
use of generative adversarial networks (GANs) for generation of images of galaxies with constraints - semi-supervised case (example: We want computer to generate an image of a certain type of galaxy. The image is close to indistinguishable from an observed image)