Practical applications of Machine Learning in modern Astronomy

17 Nov 2020, 09:00 → 18 Nov 2020, 16:00 Europe/Berlin

ZOOM (DESY)

During this interactive, online workshop, you will learn about common concepts and tools in modern ML, and work through examples of their application to problems in astronomical data analysis.

Tuesday 17 November

1 Introduction to Machine Learning: different types of machine learning algorithms, Theoretical background, practical aspects, structure and elements of (convolutional) neural networks

Speaker: Gal Matijevič

2 Unsupervised Learning I: application of t-SNE and clustering to big datasets

10:30 Break

3 Supervised Learning: practical introduction to convolutional neural networks and application to stellar magnitude regression (Part 1)

12:30 Break

4 Supervised Learning: practical introduction to convolutional neural networks and application to stellar magnitude regression (Part 2)

Wednesday 18 November

5 Unsupervised Learning II: autoencoders used on stellar spectra

10:30 Break

6 Supervised Learning II: solar image segmentation with convolutional neural networks

12:30 Break

7 Supervised Learning III: Generative Adversarial Networks (GANs) used to generate realistic galaxy images